In [2]:
pip install yfinance
Collecting yfinanceNote: you may need to restart the kernel to use updated packages.

  Obtaining dependency information for yfinance from https://files.pythonhosted.org/packages/58/f7/a966b800b49cb5379e348bf0717df481051714a99ece15289718562f6952/yfinance-0.2.35-py2.py3-none-any.whl.metadata
  Downloading yfinance-0.2.35-py2.py3-none-any.whl.metadata (11 kB)
Requirement already satisfied: pandas>=1.3.0 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from yfinance) (2.0.3)
Requirement already satisfied: numpy>=1.16.5 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from yfinance) (1.24.3)
Requirement already satisfied: requests>=2.31 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from yfinance) (2.31.0)
Collecting multitasking>=0.0.7 (from yfinance)
  Downloading multitasking-0.0.11-py3-none-any.whl (8.5 kB)
Requirement already satisfied: lxml>=4.9.1 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from yfinance) (4.9.3)
Requirement already satisfied: appdirs>=1.4.4 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from yfinance) (1.4.4)
Requirement already satisfied: pytz>=2022.5 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from yfinance) (2023.3.post1)
Collecting frozendict>=2.3.4 (from yfinance)
  Downloading frozendict-2.4.0.tar.gz (314 kB)
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  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Collecting peewee>=3.16.2 (from yfinance)
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  Installing build dependencies: started
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  Getting requirements to build wheel: finished with status 'done'
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  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: beautifulsoup4>=4.11.1 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from yfinance) (4.12.2)
Collecting html5lib>=1.1 (from yfinance)
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Building wheels for collected packages: frozendict, peewee
  Building wheel for frozendict (pyproject.toml): started
  Building wheel for frozendict (pyproject.toml): finished with status 'done'
  Created wheel for frozendict: filename=frozendict-2.4.0-py3-none-any.whl size=15471 sha256=dbf7651bc1f8bfcb525e662b880adc7d8dd7842e8ad8eba80ace9f0deaa093e7
  Stored in directory: c:\users\yasha khanna\appdata\local\pip\cache\wheels\31\dd\81\a814e6f8cde8a1bbc1f088fdc273943371f10478b91a605e14
  Building wheel for peewee (pyproject.toml): started
  Building wheel for peewee (pyproject.toml): finished with status 'done'
  Created wheel for peewee: filename=peewee-3.17.0-py3-none-any.whl size=135766 sha256=0b30a895d32ab893c63142da37cc06fc85a845df28f44e3900eb519a72f24f83
  Stored in directory: c:\users\yasha khanna\appdata\local\pip\cache\wheels\02\20\23\74a10d0cd31f5d41c19b92ddf4c138ceff01b9f4675f19dbf5
Successfully built frozendict peewee
Installing collected packages: peewee, multitasking, html5lib, frozendict, yfinance
Successfully installed frozendict-2.4.0 html5lib-1.1 multitasking-0.0.11 peewee-3.17.0 yfinance-0.2.35
In [3]:
import pandas as pd
import yfinance as yf
import datetime
from datetime import date, timedelta
today = date.today()
In [4]:
d1 = today.strftime("%Y-%m-%d")
end_date = d1
d2 = date.today() - timedelta(days=730)
d2 = d2.strftime("%Y-%m-%d")
start_date = d2

data = yf.download('BTC-USD', 
                      start=start_date, 
                      end=end_date, 
                      progress=False)
data["Date"] = data.index
data = data[["Date", "Open", "High", "Low", "Close", "Adj Close", "Volume"]]
data.reset_index(drop=True, inplace=True)
print(data.head())
        Date          Open          High           Low         Close  \
0 2022-01-18  42250.074219  42534.402344  41392.214844  42375.632812   
1 2022-01-19  42374.039062  42478.304688  41242.914062  41744.328125   
2 2022-01-20  41744.027344  43413.023438  40672.824219  40680.417969   
3 2022-01-21  40699.605469  41060.527344  35791.425781  36457.316406   
4 2022-01-22  36471.589844  36688.812500  34349.250000  35030.250000   

      Adj Close       Volume  
0  42375.632812  22417209227  
1  41744.328125  23091543258  
2  40680.417969  20382033940  
3  36457.316406  43011992031  
4  35030.250000  39714385405  
In [5]:
data.shape
Out[5]:
(730, 7)
In [6]:
import plotly.graph_objects as go
figure = go.Figure(data=[go.Candlestick(x=data["Date"],
                                        open=data["Open"], 
                                        high=data["High"],
                                        low=data["Low"], 
                                        close=data["Close"])])
figure.update_layout(title = "Bitcoin Price Analysis", 
                     xaxis_rangeslider_visible=False)
figure.show()
In [7]:
correlation = data.corr()
print(correlation["Close"].sort_values(ascending=False))
Close        1.000000
Adj Close    1.000000
High         0.997571
Low          0.997499
Open         0.994589
Date         0.045692
Volume      -0.067389
Name: Close, dtype: float64
In [9]:
pip install autots
Collecting autots
  Obtaining dependency information for autots from https://files.pythonhosted.org/packages/84/b9/2a4bd27749d9ff6f91435e4e32707b862769610ff1c0be15e4814676e569/autots-0.6.7-py3-none-any.whl.metadata
  Downloading autots-0.6.7-py3-none-any.whl.metadata (10.0 kB)
Requirement already satisfied: numpy>=1.14.6 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from autots) (1.24.3)
Requirement already satisfied: pandas>=0.25.0 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from autots) (2.0.3)
Requirement already satisfied: statsmodels>=0.10.0 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from autots) (0.14.0)
Requirement already satisfied: scikit-learn>=0.20.0 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from autots) (1.3.2)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from pandas>=0.25.0->autots) (2.8.2)
Requirement already satisfied: pytz>=2020.1 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from pandas>=0.25.0->autots) (2023.3.post1)
Requirement already satisfied: tzdata>=2022.1 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from pandas>=0.25.0->autots) (2023.3)
Requirement already satisfied: scipy>=1.5.0 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from scikit-learn>=0.20.0->autots) (1.11.1)
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Requirement already satisfied: patsy>=0.5.2 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from statsmodels>=0.10.0->autots) (0.5.3)
Requirement already satisfied: packaging>=21.3 in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from statsmodels>=0.10.0->autots) (23.1)
Requirement already satisfied: six in c:\users\yasha khanna\.conda\anaconda\lib\site-packages (from patsy>=0.5.2->statsmodels>=0.10.0->autots) (1.16.0)
Downloading autots-0.6.7-py3-none-any.whl (821 kB)
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Installing collected packages: autots
Successfully installed autots-0.6.7
Note: you may need to restart the kernel to use updated packages.
In [10]:
from autots import AutoTS
model = AutoTS(forecast_length=30, frequency='infer', ensemble='simple')
model = model.fit(data, date_col='Date', value_col='Close', id_col=None)
prediction = model.predict()
forecast = prediction.forecast
print(forecast)
Data frequency is: D, used frequency is: D
Model Number: 1 with model ARIMA in generation 0 of 10
Model Number: 2 with model AverageValueNaive in generation 0 of 10
Model Number: 3 with model AverageValueNaive in generation 0 of 10
Model Number: 4 with model AverageValueNaive in generation 0 of 10
Model Number: 5 with model DatepartRegression in generation 0 of 10
Model Number: 6 with model DatepartRegression in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\svm\_classes.py:32: FutureWarning:

The default value of `dual` will change from `True` to `'auto'` in 1.5. Set the value of `dual` explicitly to suppress the warning.

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\svm\_base.py:1250: ConvergenceWarning:

Liblinear failed to converge, increase the number of iterations.

Model Number: 7 with model DatepartRegression in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

Model Number: 8 with model DatepartRegression in generation 0 of 10
WARNING:tensorflow:From C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\keras\src\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.

WARNING:tensorflow:From C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\keras\src\backend.py:277: The name tf.reset_default_graph is deprecated. Please use tf.compat.v1.reset_default_graph instead.

WARNING:tensorflow:From C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\keras\src\optimizers\__init__.py:309: The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.

Epoch 1/50
WARNING:tensorflow:From C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\keras\src\utils\tf_utils.py:492: The name tf.ragged.RaggedTensorValue is deprecated. Please use tf.compat.v1.ragged.RaggedTensorValue instead.

22/22 [==============================] - 13s 10ms/step - loss: 0.4158
Epoch 2/50
22/22 [==============================] - 0s 10ms/step - loss: 0.4053
Epoch 3/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3955
Epoch 4/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3789
Epoch 5/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3738
Epoch 6/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3681
Epoch 7/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3655
Epoch 8/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3619
Epoch 9/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3609
Epoch 10/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3602
Epoch 11/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3579
Epoch 12/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3535
Epoch 13/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3529
Epoch 14/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3535
Epoch 15/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3515
Epoch 16/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3519
Epoch 17/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3546
Epoch 18/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3502
Epoch 19/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3491
Epoch 20/50
22/22 [==============================] - 0s 8ms/step - loss: 0.3474
Epoch 21/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3483
Epoch 22/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3451
Epoch 23/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3474
Epoch 24/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3469
Epoch 25/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3396
Epoch 26/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3451
Epoch 27/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3516
Epoch 28/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3430
Epoch 29/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3416
Epoch 30/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3433
Epoch 31/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3422
Epoch 32/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3415
Epoch 33/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3414
Epoch 34/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3379
Epoch 35/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3367
Epoch 36/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3373
Epoch 37/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3401
Epoch 38/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3382
Epoch 39/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3333
Epoch 40/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3409
Epoch 41/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3321
Epoch 42/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3337
Epoch 43/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3351
Epoch 44/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3329
Epoch 45/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3310
Epoch 46/50
22/22 [==============================] - 0s 9ms/step - loss: 0.3351
Epoch 47/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3306
Epoch 48/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3312
Epoch 49/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3242
Epoch 50/50
22/22 [==============================] - 0s 10ms/step - loss: 0.3294
1/1 [==============================] - 2s 2s/step
Model Number: 9 with model ETS in generation 0 of 10
Model Number: 10 with model ETS in generation 0 of 10
Model Number: 11 with model GLM in generation 0 of 10
Model Number: 12 with model GLM in generation 0 of 10
Model Number: 13 with model GLS in generation 0 of 10
Model Number: 14 with model GLS in generation 0 of 10
Model Number: 15 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 15 in generation 0: GluonTS
Model Number: 16 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 16 in generation 0: GluonTS
Model Number: 17 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 17 in generation 0: GluonTS
Model Number: 18 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 18 in generation 0: GluonTS
Model Number: 19 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 19 in generation 0: GluonTS
Model Number: 20 with model LastValueNaive in generation 0 of 10
Model Number: 21 with model LastValueNaive in generation 0 of 10
Model Number: 22 with model LastValueNaive in generation 0 of 10
Model Number: 23 with model LastValueNaive in generation 0 of 10
Model Number: 24 with model SeasonalNaive in generation 0 of 10
Model Number: 25 with model SeasonalNaive in generation 0 of 10
Model Number: 26 with model SeasonalNaive in generation 0 of 10
Model Number: 27 with model UnobservedComponents in generation 0 of 10
Model Number: 28 with model UnobservedComponents in generation 0 of 10
Model Number: 29 with model UnobservedComponents in generation 0 of 10
Model Number: 30 with model VAR in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VAR') in model 30 in generation 0: VAR
Model Number: 31 with model VAR in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VAR') in model 31 in generation 0: VAR
Model Number: 32 with model VECM in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VECM') in model 32 in generation 0: VECM
Model Number: 33 with model VECM in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VECM') in model 33 in generation 0: VECM
Model Number: 34 with model WindowRegression in generation 0 of 10
Model Number: 35 with model ConstantNaive in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

Model Number: 36 with model FBProphet in generation 0 of 10
Template Eval Error: ModuleNotFoundError("No module named 'fbprophet'") in model 36 in generation 0: FBProphet
Model Number: 37 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 37 in generation 0: GluonTS
Model Number: 38 with model MultivariateRegression in generation 0 of 10
Model Number: 39 with model MultivariateRegression in generation 0 of 10
Template Eval Error: ValueError("regression_type='User' but not future_regressor supplied.") in model 39 in generation 0: MultivariateRegression
Model Number: 40 with model DatepartRegression in generation 0 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor passed") in model 40 in generation 0: DatepartRegression
Model Number: 41 with model SeasonalNaive in generation 0 of 10
Model Number: 42 with model DatepartRegression in generation 0 of 10
Model Number: 43 with model UnobservedComponents in generation 0 of 10
Model Number: 44 with model UnobservedComponents in generation 0 of 10
Model Number: 45 with model ETS in generation 0 of 10
Model Number: 46 with model VECM in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VECM') in model 46 in generation 0: VECM
Model Number: 47 with model ARDL in generation 0 of 10
Model Number: 48 with model MultivariateMotif in generation 0 of 10
Model Number: 49 with model MultivariateMotif in generation 0 of 10
Model Number: 50 with model UnivariateMotif in generation 0 of 10
Model Number: 51 with model UnivariateMotif in generation 0 of 10
Model Number: 52 with model SectionalMotif in generation 0 of 10
Model Number: 53 with model SectionalMotif in generation 0 of 10
Model Number: 54 with model MultivariateRegression in generation 0 of 10
Model Number: 55 with model FBProphet in generation 0 of 10
Template Eval Error: ModuleNotFoundError("No module named 'fbprophet'") in model 55 in generation 0: FBProphet
Model Number: 56 with model SeasonalNaive in generation 0 of 10
Model Number: 57 with model DatepartRegression in generation 0 of 10
Model Number: 58 with model NVAR in generation 0 of 10
Model Number: 59 with model Theta in generation 0 of 10
Model Number: 60 with model UnivariateRegression in generation 0 of 10
Model Number: 61 with model ARCH in generation 0 of 10
Template Eval Error: ImportError('`arch` package must be installed from pip') in model 61 in generation 0: ARCH
Model Number: 62 with model ConstantNaive in generation 0 of 10
Model Number: 63 with model LastValueNaive in generation 0 of 10
Model Number: 64 with model AverageValueNaive in generation 0 of 10
Model Number: 65 with model GLS in generation 0 of 10
Model Number: 66 with model SeasonalNaive in generation 0 of 10
Model Number: 67 with model GLM in generation 0 of 10
Model Number: 68 with model ETS in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

Model Number: 69 with model FBProphet in generation 0 of 10
Template Eval Error: ModuleNotFoundError("No module named 'fbprophet'") in model 69 in generation 0: FBProphet
Model Number: 70 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 70 in generation 0: GluonTS
Model Number: 71 with model UnobservedComponents in generation 0 of 10
Model Number: 72 with model VAR in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VAR') in model 72 in generation 0: VAR
Model Number: 73 with model VECM in generation 0 of 10
Template Eval Error: LinAlgError('Singular matrix') in model 73 in generation 0: VECM
Model Number: 74 with model ARIMA in generation 0 of 10
Model Number: 75 with model WindowRegression in generation 0 of 10
Model Number: 76 with model DatepartRegression in generation 0 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor passed") in model 76 in generation 0: DatepartRegression
Model Number: 77 with model UnivariateRegression in generation 0 of 10
Model Number: 78 with model MultivariateRegression in generation 0 of 10
Model Number: 79 with model UnivariateMotif in generation 0 of 10
Model Number: 80 with model MultivariateMotif in generation 0 of 10
Model Number: 81 with model SectionalMotif in generation 0 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 81 in generation 0: SectionalMotif
Model Number: 82 with model NVAR in generation 0 of 10
Model Number: 83 with model Theta in generation 0 of 10
Model Number: 84 with model ARDL in generation 0 of 10
Model Number: 85 with model ARCH in generation 0 of 10
Template Eval Error: ImportError('`arch` package must be installed from pip') in model 85 in generation 0: ARCH
Model Number: 86 with model MetricMotif in generation 0 of 10
Model Number: 87 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 87 in generation 0: GluonTS
Model Number: 88 with model UnobservedComponents in generation 0 of 10
Model Number: 89 with model SeasonalNaive in generation 0 of 10
Model Number: 90 with model SeasonalNaive in generation 0 of 10
Model Number: 91 with model AverageValueNaive in generation 0 of 10
Model Number: 92 with model SectionalMotif in generation 0 of 10
Template Eval Error: ValueError('Unknown Distance Metric: kulsinski') in model 92 in generation 0: SectionalMotif
Model Number: 93 with model ARIMA in generation 0 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 93 in generation 0: ARIMA
Model Number: 94 with model Theta in generation 0 of 10
Model Number: 95 with model ARDL in generation 0 of 10
Model Number: 96 with model VAR in generation 0 of 10
Template Eval Error: ValueError("x contains one or more constant columns. Column(s) 1 are constant. Adding a constant with trend='c' is not allowed.") in model 96 in generation 0: VAR
Model Number: 97 with model UnivariateMotif in generation 0 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 97 in generation 0: UnivariateMotif
Model Number: 98 with model MultivariateMotif in generation 0 of 10
Model Number: 99 with model SeasonalNaive in generation 0 of 10
Model Number: 100 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 100 in generation 0: GluonTS
Model Number: 101 with model ConstantNaive in generation 0 of 10
Model Number: 102 with model SeasonalNaive in generation 0 of 10
Model Number: 103 with model AverageValueNaive in generation 0 of 10
Model Number: 104 with model VECM in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VECM') in model 104 in generation 0: VECM
Model Number: 105 with model ETS in generation 0 of 10
Model Number: 106 with model UnobservedComponents in generation 0 of 10
Model Number: 107 with model LastValueNaive in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_coordinate_descent.py:628: ConvergenceWarning:

Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.124e+08, tolerance: 3.238e+05

Model Number: 108 with model VECM in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VECM') in model 108 in generation 0: VECM
Model Number: 109 with model SectionalMotif in generation 0 of 10
Template Eval Error: ValueError('kth(=20) out of bounds (13)') in model 109 in generation 0: SectionalMotif
Model Number: 110 with model DatepartRegression in generation 0 of 10
Model Number: 111 with model SectionalMotif in generation 0 of 10
Template Eval Error: ValueError("regression_type=='User' but no future_regressor supplied") in model 111 in generation 0: SectionalMotif
Model Number: 112 with model MetricMotif in generation 0 of 10
Model Number: 113 with model Theta in generation 0 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 113 in generation 0: Theta
Model Number: 114 with model SectionalMotif in generation 0 of 10
Model Number: 115 with model NVAR in generation 0 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 115 in generation 0: NVAR
Model Number: 116 with model LastValueNaive in generation 0 of 10
Model Number: 117 with model GLS in generation 0 of 10
Model Number: 118 with model SeasonalNaive in generation 0 of 10
Model Number: 119 with model GLM in generation 0 of 10
Model Number: 120 with model GluonTS in generation 0 of 10
Template Eval Error: ImportError('GluonTS installation is incompatible with AutoTS. The numpy version is sometimes the issue, try 1.23.1 {as of 06-2023}') in model 120 in generation 0: GluonTS
Model Number: 121 with model ETS in generation 0 of 10
Model Number: 122 with model NVAR in generation 0 of 10
Model Number: 123 with model ARDL in generation 0 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 123 in generation 0: ARDL
Model Number: 124 with model GLM in generation 0 of 10
Template Eval Error: ValueError('NaN, inf or invalid value detected in weights, estimation infeasible.') in model 124 in generation 0: GLM
Model Number: 125 with model DatepartRegression in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:445: RuntimeWarning:

divide by zero encountered in divide

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:143: RuntimeWarning:

divide by zero encountered in divide

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_regression.py:500: UserWarning:

One or more samples have no neighbors within specified radius; predicting NaN.

Template Eval Error: ValueError('Model DatepartRegression returned NaN for one or more series. fail_on_forecast_nan=True') in model 125 in generation 0: DatepartRegression
Model Number: 126 with model LastValueNaive in generation 0 of 10
Model Number: 127 with model NVAR in generation 0 of 10
Model Number: 128 with model WindowRegression in generation 0 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 128 in generation 0: WindowRegression
Model Number: 129 with model MultivariateMotif in generation 0 of 10
Model Number: 130 with model Theta in generation 0 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 130 in generation 0: Theta
Model Number: 131 with model MetricMotif in generation 0 of 10
Template Eval Error: Exception('Transformer HolidayTransformer failed on fit') in model 131 in generation 0: MetricMotif
Model Number: 132 with model UnobservedComponents in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.52401e-25): result may not be accurate.

Model Number: 133 with model AverageValueNaive in generation 0 of 10
Model Number: 134 with model SectionalMotif in generation 0 of 10
Template Eval Error: ValueError('Unknown Distance Metric: kulsinski') in model 134 in generation 0: SectionalMotif
Model Number: 135 with model LastValueNaive in generation 0 of 10
Model Number: 136 with model FBProphet in generation 0 of 10
Template Eval Error: ModuleNotFoundError("No module named 'fbprophet'") in model 136 in generation 0: FBProphet
Model Number: 137 with model Theta in generation 0 of 10
Model Number: 138 with model AverageValueNaive in generation 0 of 10
Model Number: 139 with model UnivariateMotif in generation 0 of 10
Model Number: 140 with model AverageValueNaive in generation 0 of 10
Model Number: 141 with model MultivariateMotif in generation 0 of 10
Template Eval Error: IndexError('index 310 is out of bounds for axis 0 with size 1') in model 141 in generation 0: MultivariateMotif
Model Number: 142 with model DatepartRegression in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.52401e-25): result may not be accurate.

Model Number: 143 with model UnivariateMotif in generation 0 of 10
Model Number: 144 with model ARIMA in generation 0 of 10
Model Number: 145 with model MetricMotif in generation 0 of 10
Model Number: 146 with model VECM in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VECM') in model 146 in generation 0: VECM
Model Number: 147 with model ETS in generation 0 of 10
Model Number: 148 with model VECM in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VECM') in model 148 in generation 0: VECM
Model Number: 149 with model ConstantNaive in generation 0 of 10
Model Number: 150 with model VECM in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VECM') in model 150 in generation 0: VECM
Model Number: 151 with model Theta in generation 0 of 10
Model Number: 152 with model UnobservedComponents in generation 0 of 10
Template Eval Error: Exception('Transformer HolidayTransformer failed on fit') in model 152 in generation 0: UnobservedComponents
Model Number: 153 with model NVAR in generation 0 of 10
Model Number: 154 with model NVAR in generation 0 of 10
Model Number: 155 with model GLS in generation 0 of 10
Model Number: 156 with model GLM in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:1367: ValueWarning:

Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:1402: RuntimeWarning:

divide by zero encountered in divide

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:527: RuntimeWarning:

overflow encountered in exp

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:1406: RuntimeWarning:

divide by zero encountered in log

Model Number: 157 with model GLS in generation 0 of 10
Model Number: 158 with model GLM in generation 0 of 10
Template Eval Error: ValueError('regression_type=user and no future_regressor passed') in model 158 in generation 0: GLM
Model Number: 159 with model ETS in generation 0 of 10
Model Number: 160 with model GLS in generation 0 of 10
Model Number: 161 with model SectionalMotif in generation 0 of 10
Template Eval Error: ValueError("regression_type=='User' but no future_regressor supplied") in model 161 in generation 0: SectionalMotif
Model Number: 162 with model AverageValueNaive in generation 0 of 10
Model Number: 163 with model VAR in generation 0 of 10
Template Eval Error: ValueError('Only gave one variable to VAR') in model 163 in generation 0: VAR
Model Number: 164 with model DatepartRegression in generation 0 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor passed") in model 164 in generation 0: DatepartRegression
Model Number: 165 with model WindowRegression in generation 0 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor passed") in model 165 in generation 0: WindowRegression
Model Number: 166 with model GLS in generation 0 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 166 in generation 0: GLS
Model Number: 167 with model VECM in generation 0 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 167 in generation 0: VECM
Model Number: 168 with model AverageValueNaive in generation 0 of 10
Model Number: 169 with model MultivariateMotif in generation 0 of 10
Template Eval Error: Exception('Transformer HolidayTransformer failed on fit') in model 169 in generation 0: MultivariateMotif
Model Number: 170 with model UnivariateMotif in generation 0 of 10
Model Number: 171 with model ARDL in generation 0 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 171 in generation 0: ARDL
Model Number: 172 with model MultivariateMotif in generation 0 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.52401e-25): result may not be accurate.

Model Number: 173 with model VECM in generation 0 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 173 in generation 0: VECM
Model Number: 174 with model ETS in generation 0 of 10
Model Number: 175 with model Theta in generation 0 of 10
Model Number: 176 with model NVAR in generation 0 of 10
Model Number: 177 with model GLM in generation 0 of 10
Model Number: 178 with model ARCH in generation 0 of 10
Template Eval Error: ImportError('`arch` package must be installed from pip') in model 178 in generation 0: ARCH
Model Number: 179 with model ARCH in generation 0 of 10
Template Eval Error: ImportError('`arch` package must be installed from pip') in model 179 in generation 0: ARCH
Model Number: 180 with model GLS in generation 0 of 10
Model Number: 181 with model ConstantNaive in generation 0 of 10
Model Number: 182 with model ETS in generation 0 of 10
Model Number: 183 with model UnivariateMotif in generation 0 of 10
Model Number: 184 with model ETS in generation 0 of 10
Model Number: 185 with model ARCH in generation 0 of 10
Template Eval Error: ImportError('`arch` package must be installed from pip') in model 185 in generation 0: ARCH
Model Number: 186 with model AverageValueNaive in generation 0 of 10
New Generation: 1 of 10
Model Number: 187 with model MultivariateRegression in generation 1 of 10
Model Number: 188 with model Theta in generation 1 of 10
Model Number: 189 with model GLS in generation 1 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 189 in generation 1: GLS
Model Number: 190 with model UnivariateRegression in generation 1 of 10
Model Number: 191 with model AverageValueNaive in generation 1 of 10
Model Number: 192 with model SeasonalNaive in generation 1 of 10
Model Number: 193 with model LastValueNaive in generation 1 of 10
Model Number: 194 with model LastValueNaive in generation 1 of 10
Model Number: 195 with model SectionalMotif in generation 1 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 195 in generation 1: SectionalMotif
Model Number: 196 with model MultivariateRegression in generation 1 of 10
Model Number: 197 with model LastValueNaive in generation 1 of 10
Model Number: 198 with model Theta in generation 1 of 10
Model Number: 199 with model UnivariateRegression in generation 1 of 10
Model Number: 200 with model SeasonalNaive in generation 1 of 10
Model Number: 201 with model UnobservedComponents in generation 1 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 201 in generation 1: UnobservedComponents
Model Number: 202 with model SeasonalNaive in generation 1 of 10
Model Number: 203 with model GLM in generation 1 of 10
Model Number: 204 with model GLM in generation 1 of 10
Model Number: 205 with model UnivariateMotif in generation 1 of 10
Model Number: 206 with model MetricMotif in generation 1 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 206 in generation 1: MetricMotif
Model Number: 207 with model MetricMotif in generation 1 of 10
Model Number: 208 with model ETS in generation 1 of 10
Model Number: 209 with model LastValueNaive in generation 1 of 10
Model Number: 210 with model AverageValueNaive in generation 1 of 10
Model Number: 211 with model UnobservedComponents in generation 1 of 10
Model Number: 212 with model MultivariateMotif in generation 1 of 10
Model Number: 213 with model UnivariateMotif in generation 1 of 10
Model Number: 214 with model ARIMA in generation 1 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 214 in generation 1: ARIMA
Model Number: 215 with model LastValueNaive in generation 1 of 10
Model Number: 216 with model ConstantNaive in generation 1 of 10
Model Number: 217 with model UnivariateMotif in generation 1 of 10
Model Number: 218 with model LastValueNaive in generation 1 of 10
Model Number: 219 with model UnobservedComponents in generation 1 of 10
Model Number: 220 with model SectionalMotif in generation 1 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 220 in generation 1: SectionalMotif
Model Number: 221 with model Theta in generation 1 of 10
Model Number: 222 with model UnivariateMotif in generation 1 of 10
Model Number: 223 with model SeasonalNaive in generation 1 of 10
Model Number: 224 with model LastValueNaive in generation 1 of 10
Model Number: 225 with model DatepartRegression in generation 1 of 10
Model Number: 226 with model ARDL in generation 1 of 10
Model Number: 227 with model AverageValueNaive in generation 1 of 10
Model Number: 228 with model SeasonalNaive in generation 1 of 10
Model Number: 229 with model LastValueNaive in generation 1 of 10
Model Number: 230 with model UnivariateMotif in generation 1 of 10
Model Number: 231 with model UnivariateMotif in generation 1 of 10
Model Number: 232 with model MultivariateMotif in generation 1 of 10
Model Number: 233 with model ETS in generation 1 of 10
Template Eval Error: AttributeError("'DataFrame' object has no attribute 'name'") in model 233 in generation 1: ETS
Model Number: 234 with model ETS in generation 1 of 10
Model Number: 235 with model UnobservedComponents in generation 1 of 10
Model Number: 236 with model NVAR in generation 1 of 10
Model Number: 237 with model DatepartRegression in generation 1 of 10
Model Number: 238 with model UnobservedComponents in generation 1 of 10
Model Number: 239 with model Theta in generation 1 of 10
Model Number: 240 with model AverageValueNaive in generation 1 of 10
Model Number: 241 with model LastValueNaive in generation 1 of 10
Model Number: 242 with model ARIMA in generation 1 of 10
Model Number: 243 with model MetricMotif in generation 1 of 10
Model Number: 244 with model AverageValueNaive in generation 1 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 244 in generation 1: AverageValueNaive
Model Number: 245 with model LastValueNaive in generation 1 of 10
Model Number: 246 with model ETS in generation 1 of 10
Template Eval Error: AttributeError("'DataFrame' object has no attribute 'name'") in model 246 in generation 1: ETS
Model Number: 247 with model ConstantNaive in generation 1 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

Model Number: 248 with model MetricMotif in generation 1 of 10
Model Number: 249 with model LastValueNaive in generation 1 of 10
Model Number: 250 with model ETS in generation 1 of 10
Model Number: 251 with model AverageValueNaive in generation 1 of 10
Model Number: 252 with model SeasonalNaive in generation 1 of 10
Model Number: 253 with model ETS in generation 1 of 10
Model Number: 254 with model GLM in generation 1 of 10
Template Eval Error: ValueError('regression_type=user and no future_regressor passed') in model 254 in generation 1: GLM
Model Number: 255 with model UnivariateMotif in generation 1 of 10
Model Number: 256 with model MultivariateMotif in generation 1 of 10
Model Number: 257 with model AverageValueNaive in generation 1 of 10
Model Number: 258 with model DatepartRegression in generation 1 of 10
Template Eval Error: ValueError('Model DatepartRegression returned NaN for one or more series. fail_on_forecast_nan=True') in model 258 in generation 1: DatepartRegression
Model Number: 259 with model LastValueNaive in generation 1 of 10
Model Number: 260 with model ARDL in generation 1 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_regression.py:500: UserWarning:

One or more samples have no neighbors within specified radius; predicting NaN.

Model Number: 261 with model MetricMotif in generation 1 of 10
Model Number: 262 with model UnobservedComponents in generation 1 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 262 in generation 1: UnobservedComponents
Model Number: 263 with model ETS in generation 1 of 10
Model Number: 264 with model ETS in generation 1 of 10
Model Number: 265 with model UnobservedComponents in generation 1 of 10
Model Number: 266 with model SeasonalNaive in generation 1 of 10
Model Number: 267 with model NVAR in generation 1 of 10
Model Number: 268 with model DatepartRegression in generation 1 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor passed") in model 268 in generation 1: DatepartRegression
Model Number: 269 with model NVAR in generation 1 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 269 in generation 1: NVAR
Model Number: 270 with model SeasonalNaive in generation 1 of 10
Model Number: 271 with model AverageValueNaive in generation 1 of 10
Model Number: 272 with model AverageValueNaive in generation 1 of 10
Model Number: 273 with model Theta in generation 1 of 10
Model Number: 274 with model DatepartRegression in generation 1 of 10
Model Number: 275 with model LastValueNaive in generation 1 of 10
Model Number: 276 with model ConstantNaive in generation 1 of 10
Template Eval Error: Exception('Transformer BTCD failed on fit') in model 276 in generation 1: ConstantNaive
Model Number: 277 with model UnobservedComponents in generation 1 of 10
Model Number: 278 with model Theta in generation 1 of 10
Model Number: 279 with model ARDL in generation 1 of 10
Model Number: 280 with model Theta in generation 1 of 10
Model Number: 281 with model ConstantNaive in generation 1 of 10
Model Number: 282 with model WindowRegression in generation 1 of 10
Model Number: 283 with model ConstantNaive in generation 1 of 10
Model Number: 284 with model AverageValueNaive in generation 1 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

Model Number: 285 with model Theta in generation 1 of 10
Model Number: 286 with model UnobservedComponents in generation 1 of 10
Model Number: 287 with model ConstantNaive in generation 1 of 10
Model Number: 288 with model GLM in generation 1 of 10
Model Number: 289 with model UnivariateMotif in generation 1 of 10
Model Number: 290 with model ConstantNaive in generation 1 of 10
Model Number: 291 with model AverageValueNaive in generation 1 of 10
Model Number: 292 with model NVAR in generation 1 of 10
Model Number: 293 with model Theta in generation 1 of 10
Model Number: 294 with model ETS in generation 1 of 10
Model Number: 295 with model ConstantNaive in generation 1 of 10
Model Number: 296 with model DatepartRegression in generation 1 of 10
Template Eval Error: ValueError('Model DatepartRegression returned NaN for one or more series. fail_on_forecast_nan=True') in model 296 in generation 1: DatepartRegression
Model Number: 297 with model ETS in generation 1 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_regression.py:500: UserWarning:

One or more samples have no neighbors within specified radius; predicting NaN.

Model Number: 298 with model MetricMotif in generation 1 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 298 in generation 1: MetricMotif
Model Number: 299 with model Theta in generation 1 of 10
Model Number: 300 with model Theta in generation 1 of 10
Model Number: 301 with model UnobservedComponents in generation 1 of 10
Model Number: 302 with model UnivariateMotif in generation 1 of 10
Model Number: 303 with model ARIMA in generation 1 of 10
Model Number: 304 with model GLS in generation 1 of 10
Model Number: 305 with model Theta in generation 1 of 10
Model Number: 306 with model MultivariateMotif in generation 1 of 10
Model Number: 307 with model GLM in generation 1 of 10
Template Eval Error: ValueError('regression_type=user and no future_regressor passed') in model 307 in generation 1: GLM
Model Number: 308 with model GLM in generation 1 of 10
Model Number: 309 with model ARIMA in generation 1 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 309 in generation 1: ARIMA
Model Number: 310 with model UnivariateRegression in generation 1 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.50271e-25): result may not be accurate.

Model Number: 311 with model DatepartRegression in generation 1 of 10
New Generation: 2 of 10
Model Number: 312 with model UnivariateMotif in generation 2 of 10
Model Number: 313 with model AverageValueNaive in generation 2 of 10
Model Number: 314 with model AverageValueNaive in generation 2 of 10
Model Number: 315 with model AverageValueNaive in generation 2 of 10
Model Number: 316 with model UnivariateMotif in generation 2 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 316 in generation 2: UnivariateMotif
Model Number: 317 with model AverageValueNaive in generation 2 of 10
Model Number: 318 with model MultivariateMotif in generation 2 of 10
Model Number: 319 with model LastValueNaive in generation 2 of 10
Model Number: 320 with model UnobservedComponents in generation 2 of 10
Model Number: 321 with model UnobservedComponents in generation 2 of 10
Model Number: 322 with model ConstantNaive in generation 2 of 10
Model Number: 323 with model Theta in generation 2 of 10
Model Number: 324 with model MetricMotif in generation 2 of 10
Model Number: 325 with model MetricMotif in generation 2 of 10
Model Number: 326 with model ConstantNaive in generation 2 of 10
Model Number: 327 with model ConstantNaive in generation 2 of 10
Model Number: 328 with model SectionalMotif in generation 2 of 10
Model Number: 329 with model MetricMotif in generation 2 of 10
Model Number: 330 with model GLM in generation 2 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

Model Number: 331 with model Theta in generation 2 of 10
Model Number: 332 with model Theta in generation 2 of 10
Model Number: 333 with model Theta in generation 2 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 333 in generation 2: Theta
Model Number: 334 with model ARIMA in generation 2 of 10
Model Number: 335 with model LastValueNaive in generation 2 of 10
Model Number: 336 with model DatepartRegression in generation 2 of 10
Model Number: 337 with model UnivariateRegression in generation 2 of 10
Model Number: 338 with model DatepartRegression in generation 2 of 10
Model Number: 339 with model Theta in generation 2 of 10
Model Number: 340 with model LastValueNaive in generation 2 of 10
Model Number: 341 with model SeasonalNaive in generation 2 of 10
Model Number: 342 with model ETS in generation 2 of 10
Model Number: 343 with model MetricMotif in generation 2 of 10
Model Number: 344 with model MultivariateMotif in generation 2 of 10
Model Number: 345 with model MultivariateRegression in generation 2 of 10
Model Number: 346 with model UnivariateMotif in generation 2 of 10
Model Number: 347 with model ETS in generation 2 of 10
Model Number: 348 with model UnobservedComponents in generation 2 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 348 in generation 2: UnobservedComponents
Model Number: 349 with model SeasonalNaive in generation 2 of 10
Model Number: 350 with model MultivariateMotif in generation 2 of 10
Model Number: 351 with model UnivariateMotif in generation 2 of 10
Model Number: 352 with model ARIMA in generation 2 of 10
Model Number: 353 with model GLM in generation 2 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:1367: ValueWarning:

Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.

Model Number: 354 with model MetricMotif in generation 2 of 10
Model Number: 355 with model LastValueNaive in generation 2 of 10
Model Number: 356 with model DatepartRegression in generation 2 of 10
Template Eval Error: Exception('Transformer QuantileTransformer failed on fit') in model 356 in generation 2: DatepartRegression
Model Number: 357 with model ConstantNaive in generation 2 of 10
Model Number: 358 with model MetricMotif in generation 2 of 10
Model Number: 359 with model GLM in generation 2 of 10
Model Number: 360 with model ConstantNaive in generation 2 of 10
Model Number: 361 with model ARIMA in generation 2 of 10
Model Number: 362 with model ARIMA in generation 2 of 10
Template Eval Error: Exception('Transformer DatepartRegression failed on fit') in model 362 in generation 2: ARIMA
Model Number: 363 with model MultivariateRegression in generation 2 of 10
Model Number: 364 with model LastValueNaive in generation 2 of 10
Model Number: 365 with model SeasonalNaive in generation 2 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

Model Number: 366 with model AverageValueNaive in generation 2 of 10
Model Number: 367 with model SeasonalNaive in generation 2 of 10
Model Number: 368 with model LastValueNaive in generation 2 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 368 in generation 2: LastValueNaive
Model Number: 369 with model SeasonalNaive in generation 2 of 10
Model Number: 370 with model UnobservedComponents in generation 2 of 10
Model Number: 371 with model UnobservedComponents in generation 2 of 10
Model Number: 372 with model DatepartRegression in generation 2 of 10
Model Number: 373 with model MultivariateMotif in generation 2 of 10
Model Number: 374 with model Theta in generation 2 of 10
Model Number: 375 with model NVAR in generation 2 of 10
Model Number: 376 with model ConstantNaive in generation 2 of 10
Model Number: 377 with model SeasonalNaive in generation 2 of 10
Model Number: 378 with model UnobservedComponents in generation 2 of 10
Model Number: 379 with model ETS in generation 2 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 379 in generation 2: ETS
Model Number: 380 with model UnivariateMotif in generation 2 of 10
Model Number: 381 with model ETS in generation 2 of 10
Model Number: 382 with model Theta in generation 2 of 10
Model Number: 383 with model DatepartRegression in generation 2 of 10
Model Number: 384 with model UnivariateRegression in generation 2 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.50154e-25): result may not be accurate.

Model Number: 385 with model ETS in generation 2 of 10
Model Number: 386 with model NVAR in generation 2 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 386 in generation 2: NVAR
Model Number: 387 with model GLS in generation 2 of 10
Model Number: 388 with model ConstantNaive in generation 2 of 10
Model Number: 389 with model GLM in generation 2 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 389 in generation 2: GLM
Model Number: 390 with model AverageValueNaive in generation 2 of 10
Model Number: 391 with model Theta in generation 2 of 10
Model Number: 392 with model UnobservedComponents in generation 2 of 10
Template Eval Error: Exception('Transformer BTCD failed on fit') in model 392 in generation 2: UnobservedComponents
Model Number: 393 with model UnivariateMotif in generation 2 of 10
Model Number: 394 with model DatepartRegression in generation 2 of 10
Model Number: 395 with model SeasonalNaive in generation 2 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 395 in generation 2: SeasonalNaive
Model Number: 396 with model UnobservedComponents in generation 2 of 10
Model Number: 397 with model ARIMA in generation 2 of 10
Model Number: 398 with model GLS in generation 2 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 398 in generation 2: GLS
Model Number: 399 with model Theta in generation 2 of 10
Model Number: 400 with model LastValueNaive in generation 2 of 10
Model Number: 401 with model LastValueNaive in generation 2 of 10
Model Number: 402 with model UnivariateMotif in generation 2 of 10
Model Number: 403 with model UnivariateRegression in generation 2 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.50264e-25): result may not be accurate.

Model Number: 404 with model ConstantNaive in generation 2 of 10
Model Number: 405 with model LastValueNaive in generation 2 of 10
Model Number: 406 with model GLS in generation 2 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 406 in generation 2: GLS
Model Number: 407 with model UnobservedComponents in generation 2 of 10
Model Number: 408 with model ETS in generation 2 of 10
Model Number: 409 with model AverageValueNaive in generation 2 of 10
Model Number: 410 with model ConstantNaive in generation 2 of 10
Template Eval Error: Exception('Transformer MinMaxScaler failed on fit') in model 410 in generation 2: ConstantNaive
Model Number: 411 with model AverageValueNaive in generation 2 of 10
Model Number: 412 with model GLM in generation 2 of 10
Template Eval Error: ValueError('The first guess on the deviance function returned a nan.  This could be a boundary  problem and should be reported.') in model 412 in generation 2: GLM
Model Number: 413 with model AverageValueNaive in generation 2 of 10
Model Number: 414 with model AverageValueNaive in generation 2 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:1650: RuntimeWarning:

invalid value encountered in log

Model Number: 415 with model LastValueNaive in generation 2 of 10
Model Number: 416 with model MetricMotif in generation 2 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 416 in generation 2: MetricMotif
Model Number: 417 with model NVAR in generation 2 of 10
Model Number: 418 with model UnivariateMotif in generation 2 of 10
Model Number: 419 with model ETS in generation 2 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 419 in generation 2: ETS
Model Number: 420 with model DatepartRegression in generation 2 of 10
Model Number: 421 with model WindowRegression in generation 2 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.52401e-25): result may not be accurate.

Model Number: 422 with model ARIMA in generation 2 of 10
Model Number: 423 with model ETS in generation 2 of 10
Model Number: 424 with model SeasonalNaive in generation 2 of 10
Model Number: 425 with model SeasonalNaive in generation 2 of 10
Model Number: 426 with model LastValueNaive in generation 2 of 10
Model Number: 427 with model Theta in generation 2 of 10
Template Eval Error: Exception('Transformer Detrend failed on fit') in model 427 in generation 2: Theta
Model Number: 428 with model MultivariateMotif in generation 2 of 10
Model Number: 429 with model ARIMA in generation 2 of 10
Model Number: 430 with model MetricMotif in generation 2 of 10
Model Number: 431 with model ETS in generation 2 of 10
Model Number: 432 with model GLM in generation 2 of 10
Model Number: 433 with model ARIMA in generation 2 of 10
Model Number: 434 with model AverageValueNaive in generation 2 of 10
Model Number: 435 with model GLS in generation 2 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 435 in generation 2: GLS
Model Number: 436 with model MultivariateRegression in generation 2 of 10
Template Eval Error: ModuleNotFoundError("No module named 'xgboost'") in model 436 in generation 2: MultivariateRegression
New Generation: 3 of 10
Model Number: 437 with model MetricMotif in generation 3 of 10
Model Number: 438 with model SeasonalNaive in generation 3 of 10
Model Number: 439 with model LastValueNaive in generation 3 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\autots\tools\thresholding.py:204: RuntimeWarning:

overflow encountered in scalar power

Model Number: 440 with model LastValueNaive in generation 3 of 10
Model Number: 441 with model GLS in generation 3 of 10
Model Number: 442 with model ConstantNaive in generation 3 of 10
Model Number: 443 with model LastValueNaive in generation 3 of 10
Model Number: 444 with model LastValueNaive in generation 3 of 10
Model Number: 445 with model AverageValueNaive in generation 3 of 10
Model Number: 446 with model DatepartRegression in generation 3 of 10
Model Number: 447 with model LastValueNaive in generation 3 of 10
Model Number: 448 with model Theta in generation 3 of 10
Model Number: 449 with model UnivariateMotif in generation 3 of 10
Template Eval Error: Exception('Transformer QuantileTransformer failed on fit') in model 449 in generation 3: UnivariateMotif
Model Number: 450 with model ConstantNaive in generation 3 of 10
Model Number: 451 with model Theta in generation 3 of 10
Template Eval Error: Exception('Transformer QuantileTransformer failed on inverse') in model 451 in generation 3: Theta
Model Number: 452 with model SectionalMotif in generation 3 of 10
Model Number: 453 with model Theta in generation 3 of 10
Model Number: 454 with model ETS in generation 3 of 10
Model Number: 455 with model SeasonalNaive in generation 3 of 10
Model Number: 456 with model SectionalMotif in generation 3 of 10
Model Number: 457 with model DatepartRegression in generation 3 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 457 in generation 3: DatepartRegression
Model Number: 458 with model ETS in generation 3 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 458 in generation 3: ETS
Model Number: 459 with model ARIMA in generation 3 of 10
Model Number: 460 with model LastValueNaive in generation 3 of 10
Model Number: 461 with model DatepartRegression in generation 3 of 10
Model Number: 462 with model NVAR in generation 3 of 10
Model Number: 463 with model AverageValueNaive in generation 3 of 10
Model Number: 464 with model SeasonalNaive in generation 3 of 10
Model Number: 465 with model ARDL in generation 3 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 465 in generation 3: ARDL
Model Number: 466 with model UnivariateMotif in generation 3 of 10
Model Number: 467 with model ConstantNaive in generation 3 of 10
Model Number: 468 with model GLM in generation 3 of 10
Template Eval Error: ValueError('NaN, inf or invalid value detected in weights, estimation infeasible.') in model 468 in generation 3: GLM
Model Number: 469 with model MultivariateMotif in generation 3 of 10
Model Number: 470 with model GLS in generation 3 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:527: RuntimeWarning:

overflow encountered in exp

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:143: RuntimeWarning:

invalid value encountered in multiply

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\generalized_linear_model.py:1243: RuntimeWarning:

invalid value encountered in multiply

Model Number: 471 with model UnivariateMotif in generation 3 of 10
Model Number: 472 with model ETS in generation 3 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 472 in generation 3: ETS
Model Number: 473 with model GLM in generation 3 of 10
Model Number: 474 with model Theta in generation 3 of 10
Model Number: 475 with model AverageValueNaive in generation 3 of 10
Model Number: 476 with model SeasonalNaive in generation 3 of 10
Model Number: 477 with model LastValueNaive in generation 3 of 10
Model Number: 478 with model ConstantNaive in generation 3 of 10
Model Number: 479 with model UnivariateMotif in generation 3 of 10
Model Number: 480 with model MetricMotif in generation 3 of 10
Model Number: 481 with model AverageValueNaive in generation 3 of 10
Model Number: 482 with model UnivariateRegression in generation 3 of 10
Model Number: 483 with model MetricMotif in generation 3 of 10
Model Number: 484 with model UnobservedComponents in generation 3 of 10
Model Number: 485 with model MetricMotif in generation 3 of 10
Model Number: 486 with model ETS in generation 3 of 10
Model Number: 487 with model ConstantNaive in generation 3 of 10
Model Number: 488 with model LastValueNaive in generation 3 of 10
Model Number: 489 with model ConstantNaive in generation 3 of 10
Model Number: 490 with model ConstantNaive in generation 3 of 10
Model Number: 491 with model ConstantNaive in generation 3 of 10
Model Number: 492 with model DatepartRegression in generation 3 of 10
Model Number: 493 with model GLS in generation 3 of 10
Model Number: 494 with model UnivariateMotif in generation 3 of 10
Model Number: 495 with model MultivariateRegression in generation 3 of 10
Model Number: 496 with model MetricMotif in generation 3 of 10
Model Number: 497 with model ConstantNaive in generation 3 of 10
Model Number: 498 with model GLM in generation 3 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

Model Number: 499 with model UnobservedComponents in generation 3 of 10
Model Number: 500 with model SeasonalNaive in generation 3 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\svm\_classes.py:32: FutureWarning:

The default value of `dual` will change from `True` to `'auto'` in 1.5. Set the value of `dual` explicitly to suppress the warning.

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\svm\_base.py:1250: ConvergenceWarning:

Liblinear failed to converge, increase the number of iterations.

Model Number: 501 with model ETS in generation 3 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 501 in generation 3: ETS
Model Number: 502 with model MultivariateMotif in generation 3 of 10
Model Number: 503 with model MetricMotif in generation 3 of 10
Model Number: 504 with model SeasonalNaive in generation 3 of 10
Model Number: 505 with model ARIMA in generation 3 of 10
Model Number: 506 with model Theta in generation 3 of 10
Model Number: 507 with model SeasonalNaive in generation 3 of 10
Model Number: 508 with model UnobservedComponents in generation 3 of 10
Model Number: 509 with model NVAR in generation 3 of 10
Model Number: 510 with model ARIMA in generation 3 of 10
Model Number: 511 with model AverageValueNaive in generation 3 of 10
Model Number: 512 with model DatepartRegression in generation 3 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor passed") in model 512 in generation 3: DatepartRegression
Model Number: 513 with model ConstantNaive in generation 3 of 10
Model Number: 514 with model Theta in generation 3 of 10
Model Number: 515 with model NVAR in generation 3 of 10
Model Number: 516 with model WindowRegression in generation 3 of 10
Model Number: 517 with model Theta in generation 3 of 10
Template Eval Error: Exception('Transformer StandardScaler failed on fit') in model 517 in generation 3: Theta
Model Number: 518 with model AverageValueNaive in generation 3 of 10
Model Number: 519 with model AverageValueNaive in generation 3 of 10
Model Number: 520 with model ARIMA in generation 3 of 10
Model Number: 521 with model GLS in generation 3 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

Model Number: 522 with model LastValueNaive in generation 3 of 10
Model Number: 523 with model Theta in generation 3 of 10
Model Number: 524 with model SeasonalNaive in generation 3 of 10
Model Number: 525 with model MultivariateRegression in generation 3 of 10
Template Eval Error: ValueError('array must not contain infs or NaNs') in model 525 in generation 3: MultivariateRegression
Model Number: 526 with model ARDL in generation 3 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_regression.py:500: UserWarning:

One or more samples have no neighbors within specified radius; predicting NaN.

Model Number: 527 with model MultivariateRegression in generation 3 of 10
Model Number: 528 with model UnobservedComponents in generation 3 of 10
Model Number: 529 with model ARIMA in generation 3 of 10
Model Number: 530 with model UnivariateMotif in generation 3 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 530 in generation 3: UnivariateMotif
Model Number: 531 with model MultivariateMotif in generation 3 of 10
Model Number: 532 with model UnobservedComponents in generation 3 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 532 in generation 3: UnobservedComponents
Model Number: 533 with model SeasonalNaive in generation 3 of 10
Model Number: 534 with model Theta in generation 3 of 10
Model Number: 535 with model AverageValueNaive in generation 3 of 10
Model Number: 536 with model ConstantNaive in generation 3 of 10
Model Number: 537 with model UnivariateMotif in generation 3 of 10
Template Eval Error: ValueError('Model UnivariateMotif returned NaN for one or more series. fail_on_forecast_nan=True') in model 537 in generation 3: UnivariateMotif
Model Number: 538 with model UnobservedComponents in generation 3 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 538 in generation 3: UnobservedComponents
Model Number: 539 with model SeasonalNaive in generation 3 of 10
Model Number: 540 with model GLS in generation 3 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\numpy\lib\function_base.py:551: RuntimeWarning:

invalid value encountered in divide

Model Number: 541 with model DatepartRegression in generation 3 of 10
Model Number: 542 with model DatepartRegression in generation 3 of 10
Model Number: 543 with model SeasonalNaive in generation 3 of 10
Model Number: 544 with model AverageValueNaive in generation 3 of 10
Model Number: 545 with model Theta in generation 3 of 10
Model Number: 546 with model DatepartRegression in generation 3 of 10
Model Number: 547 with model DatepartRegression in generation 3 of 10
Model Number: 548 with model UnobservedComponents in generation 3 of 10
Model Number: 549 with model ARDL in generation 3 of 10
Model Number: 550 with model UnivariateMotif in generation 3 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 550 in generation 3: UnivariateMotif
Model Number: 551 with model Theta in generation 3 of 10
Model Number: 552 with model AverageValueNaive in generation 3 of 10
Model Number: 553 with model ARDL in generation 3 of 10
Model Number: 554 with model MultivariateRegression in generation 3 of 10
Model Number: 555 with model MetricMotif in generation 3 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 555 in generation 3: MetricMotif
Model Number: 556 with model Theta in generation 3 of 10
Model Number: 557 with model GLS in generation 3 of 10
Model Number: 558 with model MetricMotif in generation 3 of 10
Model Number: 559 with model MetricMotif in generation 3 of 10
Model Number: 560 with model ConstantNaive in generation 3 of 10
Model Number: 561 with model LastValueNaive in generation 3 of 10
New Generation: 4 of 10
Model Number: 562 with model NVAR in generation 4 of 10
Model Number: 563 with model UnivariateMotif in generation 4 of 10
Model Number: 564 with model DatepartRegression in generation 4 of 10
Model Number: 565 with model UnivariateMotif in generation 4 of 10
Model Number: 566 with model SeasonalNaive in generation 4 of 10
Model Number: 567 with model MultivariateRegression in generation 4 of 10
Model Number: 568 with model ARIMA in generation 4 of 10
Model Number: 569 with model Theta in generation 4 of 10
Model Number: 570 with model ETS in generation 4 of 10
Model Number: 571 with model GLM in generation 4 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 571 in generation 4: GLM
Model Number: 572 with model LastValueNaive in generation 4 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\decomposition\_fastica.py:576: UserWarning:

Ignoring n_components with whiten=False.

Model Number: 573 with model DatepartRegression in generation 4 of 10
Model Number: 574 with model LastValueNaive in generation 4 of 10
Model Number: 575 with model Theta in generation 4 of 10
Model Number: 576 with model Theta in generation 4 of 10
Model Number: 577 with model ARIMA in generation 4 of 10
Model Number: 578 with model MultivariateMotif in generation 4 of 10
Model Number: 579 with model GLS in generation 4 of 10
Model Number: 580 with model ETS in generation 4 of 10
Model Number: 581 with model NVAR in generation 4 of 10
Model Number: 582 with model ARIMA in generation 4 of 10
Model Number: 583 with model ARIMA in generation 4 of 10
Model Number: 584 with model AverageValueNaive in generation 4 of 10
Model Number: 585 with model GLM in generation 4 of 10
Template Eval Error: ValueError('regression_type=user and no future_regressor passed') in model 585 in generation 4: GLM
Model Number: 586 with model ETS in generation 4 of 10
Model Number: 587 with model Theta in generation 4 of 10
Model Number: 588 with model MultivariateMotif in generation 4 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 588 in generation 4: MultivariateMotif
Model Number: 589 with model ConstantNaive in generation 4 of 10
Template Eval Error: ValueError("Model returned NaN due to a preprocessing transformer {'fillna': 'rolling_mean_24', 'transformations': {'0': 'AlignLastValue', '1': 'bkfilter'}, 'transformation_params': {'0': {'rows': 1, 'lag': 1, 'method': 'multiplicative', 'strength': 1.0, 'first_value_only': False}, '1': {}}}. fail_on_forecast_nan=True") in model 589 in generation 4: ConstantNaive
Model Number: 590 with model AverageValueNaive in generation 4 of 10
Model Number: 591 with model GLS in generation 4 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 591 in generation 4: GLS
Model Number: 592 with model NVAR in generation 4 of 10
Model Number: 593 with model ETS in generation 4 of 10
Model Number: 594 with model MetricMotif in generation 4 of 10
Model Number: 595 with model UnivariateMotif in generation 4 of 10
Model Number: 596 with model MetricMotif in generation 4 of 10
Model Number: 597 with model ConstantNaive in generation 4 of 10
Model Number: 598 with model SectionalMotif in generation 4 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 598 in generation 4: SectionalMotif
Model Number: 599 with model AverageValueNaive in generation 4 of 10
Model Number: 600 with model LastValueNaive in generation 4 of 10
Model Number: 601 with model ARIMA in generation 4 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 601 in generation 4: ARIMA
Model Number: 602 with model UnobservedComponents in generation 4 of 10
Model Number: 603 with model MultivariateMotif in generation 4 of 10
Model Number: 604 with model AverageValueNaive in generation 4 of 10
Model Number: 605 with model DatepartRegression in generation 4 of 10
Model Number: 606 with model Theta in generation 4 of 10
Model Number: 607 with model LastValueNaive in generation 4 of 10
Model Number: 608 with model GLM in generation 4 of 10
Model Number: 609 with model ConstantNaive in generation 4 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 609 in generation 4: ConstantNaive
Model Number: 610 with model ConstantNaive in generation 4 of 10
Template Eval Error: Exception('Transformer StandardScaler failed on fit') in model 610 in generation 4: ConstantNaive
Model Number: 611 with model GLM in generation 4 of 10
Model Number: 612 with model UnivariateMotif in generation 4 of 10
Model Number: 613 with model AverageValueNaive in generation 4 of 10
Model Number: 614 with model UnivariateMotif in generation 4 of 10
Model Number: 615 with model ARDL in generation 4 of 10
Model Number: 616 with model AverageValueNaive in generation 4 of 10
Model Number: 617 with model UnobservedComponents in generation 4 of 10
Model Number: 618 with model ConstantNaive in generation 4 of 10
Model Number: 619 with model LastValueNaive in generation 4 of 10
Model Number: 620 with model ARIMA in generation 4 of 10
Model Number: 621 with model ARDL in generation 4 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 621 in generation 4: ARDL
Model Number: 622 with model MultivariateMotif in generation 4 of 10
Model Number: 623 with model GLS in generation 4 of 10
Model Number: 624 with model ARIMA in generation 4 of 10
Model Number: 625 with model LastValueNaive in generation 4 of 10
Model Number: 626 with model UnivariateMotif in generation 4 of 10
Template Eval Error: ValueError('Model UnivariateMotif returned NaN for one or more series. fail_on_forecast_nan=True') in model 626 in generation 4: UnivariateMotif
Model Number: 627 with model ConstantNaive in generation 4 of 10
Model Number: 628 with model ConstantNaive in generation 4 of 10
Model Number: 629 with model DatepartRegression in generation 4 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\numpy\lib\function_base.py:551: RuntimeWarning:

invalid value encountered in divide

Model Number: 630 with model MetricMotif in generation 4 of 10
Model Number: 631 with model GLM in generation 4 of 10
Template Eval Error: ValueError('NaN, inf or invalid value detected in weights, estimation infeasible.') in model 631 in generation 4: GLM
Model Number: 632 with model Theta in generation 4 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:445: RuntimeWarning:

divide by zero encountered in divide

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:143: RuntimeWarning:

divide by zero encountered in divide

Model Number: 633 with model MultivariateRegression in generation 4 of 10
Model Number: 634 with model SeasonalNaive in generation 4 of 10
Model Number: 635 with model LastValueNaive in generation 4 of 10
Model Number: 636 with model DatepartRegression in generation 4 of 10
Model Number: 637 with model UnivariateRegression in generation 4 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

Model Number: 638 with model GLM in generation 4 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

Model Number: 639 with model UnobservedComponents in generation 4 of 10
Model Number: 640 with model MultivariateRegression in generation 4 of 10
Model Number: 641 with model NVAR in generation 4 of 10
Model Number: 642 with model SeasonalNaive in generation 4 of 10
Model Number: 643 with model SectionalMotif in generation 4 of 10
Model Number: 644 with model AverageValueNaive in generation 4 of 10
Model Number: 645 with model SeasonalNaive in generation 4 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 645 in generation 4: SeasonalNaive
Model Number: 646 with model SeasonalNaive in generation 4 of 10
Model Number: 647 with model UnivariateRegression in generation 4 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.9111e-41): result may not be accurate.

Model Number: 648 with model DatepartRegression in generation 4 of 10
Model Number: 649 with model UnivariateRegression in generation 4 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 649 in generation 4: UnivariateRegression
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_coordinate_descent.py:628: ConvergenceWarning:

Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 0.000e+00, tolerance: 0.000e+00

Model Number: 650 with model LastValueNaive in generation 4 of 10
Model Number: 651 with model AverageValueNaive in generation 4 of 10
Model Number: 652 with model ETS in generation 4 of 10
Model Number: 653 with model NVAR in generation 4 of 10
Template Eval Error: Exception('Transformer MinMaxScaler failed on fit') in model 653 in generation 4: NVAR
Model Number: 654 with model UnivariateMotif in generation 4 of 10
Model Number: 655 with model ARDL in generation 4 of 10
Model Number: 656 with model DatepartRegression in generation 4 of 10
Model Number: 657 with model SeasonalNaive in generation 4 of 10
Model Number: 658 with model UnivariateMotif in generation 4 of 10
Model Number: 659 with model WindowRegression in generation 4 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

Model Number: 660 with model MultivariateRegression in generation 4 of 10
Model Number: 661 with model GLM in generation 4 of 10
Model Number: 662 with model SeasonalNaive in generation 4 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 662 in generation 4: SeasonalNaive
Model Number: 663 with model ARIMA in generation 4 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\generalized_linear_model.py:307: DomainWarning:

The InversePower link function does not respect the domain of the Gamma family.

Model Number: 664 with model UnobservedComponents in generation 4 of 10
Template Eval Error: Exception('Transformer QuantileTransformer failed on fit') in model 664 in generation 4: UnobservedComponents
Model Number: 665 with model AverageValueNaive in generation 4 of 10
Model Number: 666 with model MetricMotif in generation 4 of 10
Model Number: 667 with model UnivariateMotif in generation 4 of 10
Model Number: 668 with model LastValueNaive in generation 4 of 10
Model Number: 669 with model UnivariateMotif in generation 4 of 10
Model Number: 670 with model AverageValueNaive in generation 4 of 10
Model Number: 671 with model ConstantNaive in generation 4 of 10
Model Number: 672 with model UnivariateMotif in generation 4 of 10
Model Number: 673 with model GLM in generation 4 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 673 in generation 4: GLM
Model Number: 674 with model SeasonalNaive in generation 4 of 10
Model Number: 675 with model ARIMA in generation 4 of 10
Model Number: 676 with model LastValueNaive in generation 4 of 10
Model Number: 677 with model LastValueNaive in generation 4 of 10
Model Number: 678 with model ARIMA in generation 4 of 10
Model Number: 679 with model GLS in generation 4 of 10
Model Number: 680 with model ConstantNaive in generation 4 of 10
Model Number: 681 with model AverageValueNaive in generation 4 of 10
Model Number: 682 with model LastValueNaive in generation 4 of 10
Model Number: 683 with model ARDL in generation 4 of 10
Model Number: 684 with model Theta in generation 4 of 10
Model Number: 685 with model AverageValueNaive in generation 4 of 10
Model Number: 686 with model NVAR in generation 4 of 10
New Generation: 5 of 10
Model Number: 687 with model MetricMotif in generation 5 of 10
Model Number: 688 with model DatepartRegression in generation 5 of 10
Template Eval Error: Exception('Transformer BTCD failed on fit') in model 688 in generation 5: DatepartRegression
Model Number: 689 with model Theta in generation 5 of 10
Model Number: 690 with model DatepartRegression in generation 5 of 10
Model Number: 691 with model WindowRegression in generation 5 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 691 in generation 5: WindowRegression
Model Number: 692 with model Theta in generation 5 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 692 in generation 5: Theta
Model Number: 693 with model GLS in generation 5 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 693 in generation 5: GLS
Model Number: 694 with model GLS in generation 5 of 10
Model Number: 695 with model ConstantNaive in generation 5 of 10
Model Number: 696 with model GLM in generation 5 of 10
Model Number: 697 with model GLM in generation 5 of 10
Model Number: 698 with model AverageValueNaive in generation 5 of 10
Model Number: 699 with model ARIMA in generation 5 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 699 in generation 5: ARIMA
Model Number: 700 with model MetricMotif in generation 5 of 10
Model Number: 701 with model ARDL in generation 5 of 10
Model Number: 702 with model NVAR in generation 5 of 10
Model Number: 703 with model LastValueNaive in generation 5 of 10
Template Eval Error: Exception('Transformer BTCD failed on fit') in model 703 in generation 5: LastValueNaive
Model Number: 704 with model GLM in generation 5 of 10
Model Number: 705 with model ConstantNaive in generation 5 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 705 in generation 5: ConstantNaive
Model Number: 706 with model UnobservedComponents in generation 5 of 10
Model Number: 707 with model AverageValueNaive in generation 5 of 10
Model Number: 708 with model MetricMotif in generation 5 of 10
Model Number: 709 with model ARDL in generation 5 of 10
Template Eval Error: ValueError("ARDL series Close failed with error ValueError('integer orders must be at least 1 when causal is True.') exog train             year  month  day  weekday\nDate                                 \n2022-01-18  2022      1   18        1\n2022-01-19  2022      1   19        2\n2022-01-20  2022      1   20        3\n2022-01-21  2022      1   21        4\n2022-01-22  2022      1   22        5\n...          ...    ...  ...      ...\n2023-12-14  2023     12   14        3\n2023-12-15  2023     12   15        4\n2023-12-16  2023     12   16        5\n2023-12-17  2023     12   17        6\n2023-12-18  2023     12   18        0\n\n[700 rows x 4 columns] and predict             year  month  day  weekday\n2023-12-19  2023     12   19        1\n2023-12-20  2023     12   20        2\n2023-12-21  2023     12   21        3\n2023-12-22  2023     12   22        4\n2023-12-23  2023     12   23        5\n2023-12-24  2023     12   24        6\n2023-12-25  2023     12   25        0\n2023-12-26  2023     12   26        1\n2023-12-27  2023     12   27        2\n2023-12-28  2023     12   28        3\n2023-12-29  2023     12   29        4\n2023-12-30  2023     12   30        5\n2023-12-31  2023     12   31        6\n2024-01-01  2024      1    1        0\n2024-01-02  2024      1    2        1\n2024-01-03  2024      1    3        2\n2024-01-04  2024      1    4        3\n2024-01-05  2024      1    5        4\n2024-01-06  2024      1    6        5\n2024-01-07  2024      1    7        6\n2024-01-08  2024      1    8        0\n2024-01-09  2024      1    9        1\n2024-01-10  2024      1   10        2\n2024-01-11  2024      1   11        3\n2024-01-12  2024      1   12        4\n2024-01-13  2024      1   13        5\n2024-01-14  2024      1   14        6\n2024-01-15  2024      1   15        0\n2024-01-16  2024      1   16        1\n2024-01-17  2024      1   17        2") in model 709 in generation 5: ARDL
Model Number: 710 with model UnobservedComponents in generation 5 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 710 in generation 5: UnobservedComponents
Model Number: 711 with model NVAR in generation 5 of 10
Model Number: 712 with model SeasonalNaive in generation 5 of 10
Model Number: 713 with model UnivariateMotif in generation 5 of 10
Model Number: 714 with model LastValueNaive in generation 5 of 10
Model Number: 715 with model LastValueNaive in generation 5 of 10
Model Number: 716 with model MultivariateRegression in generation 5 of 10
Model Number: 717 with model UnobservedComponents in generation 5 of 10
Model Number: 718 with model ARIMA in generation 5 of 10
Model Number: 719 with model Theta in generation 5 of 10
Model Number: 720 with model LastValueNaive in generation 5 of 10
Model Number: 721 with model AverageValueNaive in generation 5 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 721 in generation 5: AverageValueNaive
Model Number: 722 with model ARDL in generation 5 of 10
Model Number: 723 with model LastValueNaive in generation 5 of 10
Model Number: 724 with model UnivariateMotif in generation 5 of 10
Model Number: 725 with model MetricMotif in generation 5 of 10
Model Number: 726 with model UnivariateRegression in generation 5 of 10
Template Eval Error: ValueError("regression_type='User' but not future_regressor supplied.") in model 726 in generation 5: UnivariateRegression
Model Number: 727 with model MultivariateMotif in generation 5 of 10
Model Number: 728 with model ARIMA in generation 5 of 10
Model Number: 729 with model NVAR in generation 5 of 10
Model Number: 730 with model Theta in generation 5 of 10
Model Number: 731 with model ARIMA in generation 5 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 731 in generation 5: ARIMA
Model Number: 732 with model MetricMotif in generation 5 of 10
Model Number: 733 with model ARIMA in generation 5 of 10
Model Number: 734 with model ARIMA in generation 5 of 10
Model Number: 735 with model Theta in generation 5 of 10
Model Number: 736 with model AverageValueNaive in generation 5 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 736 in generation 5: AverageValueNaive
Model Number: 737 with model UnobservedComponents in generation 5 of 10
Model Number: 738 with model LastValueNaive in generation 5 of 10
Model Number: 739 with model UnobservedComponents in generation 5 of 10
Model Number: 740 with model Theta in generation 5 of 10
Model Number: 741 with model MultivariateRegression in generation 5 of 10
Model Number: 742 with model Theta in generation 5 of 10
Model Number: 743 with model ARDL in generation 5 of 10
Model Number: 744 with model ARDL in generation 5 of 10
Model Number: 745 with model SeasonalNaive in generation 5 of 10
Model Number: 746 with model UnivariateMotif in generation 5 of 10
Model Number: 747 with model AverageValueNaive in generation 5 of 10
Model Number: 748 with model ARDL in generation 5 of 10
Model Number: 749 with model NVAR in generation 5 of 10
Model Number: 750 with model WindowRegression in generation 5 of 10
Model Number: 751 with model UnobservedComponents in generation 5 of 10
Model Number: 752 with model MetricMotif in generation 5 of 10
Model Number: 753 with model NVAR in generation 5 of 10
Model Number: 754 with model GLS in generation 5 of 10
Model Number: 755 with model SectionalMotif in generation 5 of 10
Model Number: 756 with model LastValueNaive in generation 5 of 10
Model Number: 757 with model LastValueNaive in generation 5 of 10
Model Number: 758 with model ConstantNaive in generation 5 of 10
Model Number: 759 with model ARIMA in generation 5 of 10
Model Number: 760 with model AverageValueNaive in generation 5 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 760 in generation 5: AverageValueNaive
Model Number: 761 with model AverageValueNaive in generation 5 of 10
Model Number: 762 with model ARDL in generation 5 of 10
Model Number: 763 with model NVAR in generation 5 of 10
Model Number: 764 with model ConstantNaive in generation 5 of 10
Model Number: 765 with model NVAR in generation 5 of 10
Model Number: 766 with model Theta in generation 5 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\decomposition\_fastica.py:576: UserWarning:

Ignoring n_components with whiten=False.

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\decomposition\_fastica.py:128: ConvergenceWarning:

FastICA did not converge. Consider increasing tolerance or the maximum number of iterations.

Model Number: 767 with model MultivariateRegression in generation 5 of 10
Model Number: 768 with model GLS in generation 5 of 10
Model Number: 769 with model AverageValueNaive in generation 5 of 10
Model Number: 770 with model MetricMotif in generation 5 of 10
Model Number: 771 with model AverageValueNaive in generation 5 of 10
Model Number: 772 with model SeasonalNaive in generation 5 of 10
Model Number: 773 with model SeasonalNaive in generation 5 of 10
Model Number: 774 with model NVAR in generation 5 of 10
Model Number: 775 with model ARIMA in generation 5 of 10
Model Number: 776 with model ConstantNaive in generation 5 of 10
Model Number: 777 with model MetricMotif in generation 5 of 10
Model Number: 778 with model UnivariateMotif in generation 5 of 10
Model Number: 779 with model UnobservedComponents in generation 5 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 779 in generation 5: UnobservedComponents
Model Number: 780 with model ARIMA in generation 5 of 10
Model Number: 781 with model ARDL in generation 5 of 10
Model Number: 782 with model ConstantNaive in generation 5 of 10
Model Number: 783 with model ARIMA in generation 5 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 783 in generation 5: ARIMA
Model Number: 784 with model AverageValueNaive in generation 5 of 10
Model Number: 785 with model ARDL in generation 5 of 10
Model Number: 786 with model SeasonalNaive in generation 5 of 10
New Generation: 6 of 10
Model Number: 787 with model ARDL in generation 6 of 10
Model Number: 788 with model Theta in generation 6 of 10
Model Number: 789 with model LastValueNaive in generation 6 of 10
Model Number: 790 with model ARDL in generation 6 of 10
Model Number: 791 with model NVAR in generation 6 of 10
Model Number: 792 with model MetricMotif in generation 6 of 10
Model Number: 793 with model AverageValueNaive in generation 6 of 10
Model Number: 794 with model AverageValueNaive in generation 6 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 794 in generation 6: AverageValueNaive
Model Number: 795 with model GLM in generation 6 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

Model Number: 796 with model AverageValueNaive in generation 6 of 10
Model Number: 797 with model ARDL in generation 6 of 10
Model Number: 798 with model LastValueNaive in generation 6 of 10
Model Number: 799 with model NVAR in generation 6 of 10
Model Number: 800 with model SectionalMotif in generation 6 of 10
Model Number: 801 with model Theta in generation 6 of 10
Model Number: 802 with model MetricMotif in generation 6 of 10
Model Number: 803 with model UnivariateMotif in generation 6 of 10
Model Number: 804 with model ARIMA in generation 6 of 10
Model Number: 805 with model MetricMotif in generation 6 of 10
Model Number: 806 with model SeasonalNaive in generation 6 of 10
Model Number: 807 with model DatepartRegression in generation 6 of 10
Model Number: 808 with model MetricMotif in generation 6 of 10
Model Number: 809 with model ARDL in generation 6 of 10
Model Number: 810 with model SeasonalNaive in generation 6 of 10
Model Number: 811 with model MetricMotif in generation 6 of 10
Model Number: 812 with model Theta in generation 6 of 10
Model Number: 813 with model UnobservedComponents in generation 6 of 10
Model Number: 814 with model Theta in generation 6 of 10
Model Number: 815 with model MultivariateRegression in generation 6 of 10
Template Eval Error: ModuleNotFoundError("No module named 'lightgbm'") in model 815 in generation 6: MultivariateRegression
Model Number: 816 with model ETS in generation 6 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 816 in generation 6: ETS
Model Number: 817 with model MetricMotif in generation 6 of 10
Model Number: 818 with model AverageValueNaive in generation 6 of 10
Model Number: 819 with model GLS in generation 6 of 10
Model Number: 820 with model ARDL in generation 6 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:691: ConvergenceWarning:

Stochastic Optimizer: Maximum iterations (250) reached and the optimization hasn't converged yet.

Model Number: 821 with model ARIMA in generation 6 of 10
Model Number: 822 with model ETS in generation 6 of 10
Model Number: 823 with model SectionalMotif in generation 6 of 10
Model Number: 824 with model MultivariateMotif in generation 6 of 10
Model Number: 825 with model MetricMotif in generation 6 of 10
Model Number: 826 with model AverageValueNaive in generation 6 of 10
Model Number: 827 with model GLS in generation 6 of 10
Model Number: 828 with model UnivariateRegression in generation 6 of 10
Model Number: 829 with model ConstantNaive in generation 6 of 10
Model Number: 830 with model ConstantNaive in generation 6 of 10
Model Number: 831 with model UnobservedComponents in generation 6 of 10
Model Number: 832 with model ConstantNaive in generation 6 of 10
Model Number: 833 with model ETS in generation 6 of 10
Model Number: 834 with model DatepartRegression in generation 6 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor passed") in model 834 in generation 6: DatepartRegression
Model Number: 835 with model UnivariateRegression in generation 6 of 10
Model Number: 836 with model LastValueNaive in generation 6 of 10
Model Number: 837 with model UnivariateMotif in generation 6 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.9111e-41): result may not be accurate.

Model Number: 838 with model Theta in generation 6 of 10
Model Number: 839 with model MetricMotif in generation 6 of 10
Model Number: 840 with model GLS in generation 6 of 10
Model Number: 841 with model MetricMotif in generation 6 of 10
Model Number: 842 with model GLM in generation 6 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 842 in generation 6: GLM
Model Number: 843 with model UnobservedComponents in generation 6 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 843 in generation 6: UnobservedComponents
Model Number: 844 with model ARDL in generation 6 of 10
Model Number: 845 with model NVAR in generation 6 of 10
Model Number: 846 with model LastValueNaive in generation 6 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_coordinate_descent.py:628: ConvergenceWarning:

Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.165e+09, tolerance: 4.344e+06

Model Number: 847 with model AverageValueNaive in generation 6 of 10
Model Number: 848 with model LastValueNaive in generation 6 of 10
Model Number: 849 with model NVAR in generation 6 of 10
Model Number: 850 with model LastValueNaive in generation 6 of 10
Model Number: 851 with model ARIMA in generation 6 of 10
Model Number: 852 with model AverageValueNaive in generation 6 of 10
Model Number: 853 with model SeasonalNaive in generation 6 of 10
Model Number: 854 with model Theta in generation 6 of 10
Model Number: 855 with model NVAR in generation 6 of 10
Model Number: 856 with model MultivariateMotif in generation 6 of 10
Model Number: 857 with model Theta in generation 6 of 10
Model Number: 858 with model SeasonalNaive in generation 6 of 10
Model Number: 859 with model ARIMA in generation 6 of 10
Model Number: 860 with model ARDL in generation 6 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 860 in generation 6: ARDL
Model Number: 861 with model AverageValueNaive in generation 6 of 10
Template Eval Error: Exception('Transformer RegressionFilter failed on fit') in model 861 in generation 6: AverageValueNaive
Model Number: 862 with model MultivariateMotif in generation 6 of 10
Model Number: 863 with model ARDL in generation 6 of 10
Model Number: 864 with model ConstantNaive in generation 6 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 864 in generation 6: ConstantNaive
Model Number: 865 with model WindowRegression in generation 6 of 10
Template Eval Error: ModuleNotFoundError("No module named 'lightgbm'") in model 865 in generation 6: WindowRegression
Model Number: 866 with model ARIMA in generation 6 of 10
Model Number: 867 with model Theta in generation 6 of 10
Template Eval Error: Exception('Transformer StandardScaler failed on inverse') in model 867 in generation 6: Theta
Model Number: 868 with model ARDL in generation 6 of 10
Model Number: 869 with model UnivariateMotif in generation 6 of 10
Model Number: 870 with model SeasonalNaive in generation 6 of 10
Model Number: 871 with model NVAR in generation 6 of 10
Model Number: 872 with model LastValueNaive in generation 6 of 10
Model Number: 873 with model UnivariateMotif in generation 6 of 10
Model Number: 874 with model GLM in generation 6 of 10
Template Eval Error: ValueError('NaN, inf or invalid value detected in weights, estimation infeasible.') in model 874 in generation 6: GLM
Model Number: 875 with model ARIMA in generation 6 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:445: RuntimeWarning:

divide by zero encountered in divide

C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\family.py:143: RuntimeWarning:

divide by zero encountered in divide

Model Number: 876 with model ConstantNaive in generation 6 of 10
Model Number: 877 with model UnobservedComponents in generation 6 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 877 in generation 6: UnobservedComponents
Model Number: 878 with model UnobservedComponents in generation 6 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 878 in generation 6: UnobservedComponents
Model Number: 879 with model Theta in generation 6 of 10
Model Number: 880 with model ConstantNaive in generation 6 of 10
Model Number: 881 with model UnivariateMotif in generation 6 of 10
Model Number: 882 with model SectionalMotif in generation 6 of 10
Model Number: 883 with model ETS in generation 6 of 10
Model Number: 884 with model GLM in generation 6 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

Model Number: 885 with model ETS in generation 6 of 10
Model Number: 886 with model UnobservedComponents in generation 6 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 886 in generation 6: UnobservedComponents
New Generation: 7 of 10
Model Number: 887 with model UnobservedComponents in generation 7 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 887 in generation 7: UnobservedComponents
Model Number: 888 with model ConstantNaive in generation 7 of 10
Model Number: 889 with model UnivariateMotif in generation 7 of 10
Model Number: 890 with model ConstantNaive in generation 7 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 890 in generation 7: ConstantNaive
Model Number: 891 with model GLS in generation 7 of 10
Model Number: 892 with model NVAR in generation 7 of 10
Model Number: 893 with model SeasonalNaive in generation 7 of 10
Model Number: 894 with model SeasonalNaive in generation 7 of 10
Model Number: 895 with model AverageValueNaive in generation 7 of 10
Model Number: 896 with model AverageValueNaive in generation 7 of 10
Model Number: 897 with model NVAR in generation 7 of 10
Model Number: 898 with model AverageValueNaive in generation 7 of 10
Model Number: 899 with model DatepartRegression in generation 7 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 899 in generation 7: DatepartRegression
Model Number: 900 with model ARIMA in generation 7 of 10
Model Number: 901 with model UnivariateMotif in generation 7 of 10
Model Number: 902 with model Theta in generation 7 of 10
Model Number: 903 with model GLM in generation 7 of 10
Model Number: 904 with model NVAR in generation 7 of 10
Model Number: 905 with model WindowRegression in generation 7 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\generalized_linear_model.py:307: DomainWarning:

The InversePower link function does not respect the domain of the Gamma family.

Model Number: 906 with model SeasonalNaive in generation 7 of 10
Model Number: 907 with model LastValueNaive in generation 7 of 10
Model Number: 908 with model SectionalMotif in generation 7 of 10
Model Number: 909 with model UnivariateMotif in generation 7 of 10
Model Number: 910 with model GLM in generation 7 of 10
Model Number: 911 with model Theta in generation 7 of 10
Model Number: 912 with model UnivariateRegression in generation 7 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 912 in generation 7: UnivariateRegression
Model Number: 913 with model ConstantNaive in generation 7 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

Model Number: 914 with model UnivariateRegression in generation 7 of 10
Model Number: 915 with model WindowRegression in generation 7 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 915 in generation 7: WindowRegression
Model Number: 916 with model ConstantNaive in generation 7 of 10
Model Number: 917 with model ARIMA in generation 7 of 10
Model Number: 918 with model ConstantNaive in generation 7 of 10
Model Number: 919 with model SectionalMotif in generation 7 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 919 in generation 7: SectionalMotif
Model Number: 920 with model UnobservedComponents in generation 7 of 10
Model Number: 921 with model AverageValueNaive in generation 7 of 10
Model Number: 922 with model AverageValueNaive in generation 7 of 10
Template Eval Error: Exception('Transformer BTCD failed on fit') in model 922 in generation 7: AverageValueNaive
Model Number: 923 with model GLM in generation 7 of 10
Model Number: 924 with model GLS in generation 7 of 10
Model Number: 925 with model ConstantNaive in generation 7 of 10
Model Number: 926 with model AverageValueNaive in generation 7 of 10
Model Number: 927 with model SeasonalNaive in generation 7 of 10
Model Number: 928 with model SectionalMotif in generation 7 of 10
Template Eval Error: ValueError('Unknown Distance Metric: kulsinski') in model 928 in generation 7: SectionalMotif
Model Number: 929 with model NVAR in generation 7 of 10
Model Number: 930 with model NVAR in generation 7 of 10
Model Number: 931 with model ARDL in generation 7 of 10
Model Number: 932 with model UnivariateMotif in generation 7 of 10
Model Number: 933 with model ARIMA in generation 7 of 10
Model Number: 934 with model ARDL in generation 7 of 10
Model Number: 935 with model AverageValueNaive in generation 7 of 10
Model Number: 936 with model Theta in generation 7 of 10
Template Eval Error: Exception('Transformer Detrend failed on fit') in model 936 in generation 7: Theta
Model Number: 937 with model NVAR in generation 7 of 10
Model Number: 938 with model MetricMotif in generation 7 of 10
Model Number: 939 with model GLS in generation 7 of 10
Model Number: 940 with model LastValueNaive in generation 7 of 10
Model Number: 941 with model ConstantNaive in generation 7 of 10
Model Number: 942 with model ETS in generation 7 of 10
Model Number: 943 with model AverageValueNaive in generation 7 of 10
Model Number: 944 with model ARDL in generation 7 of 10
Model Number: 945 with model UnivariateMotif in generation 7 of 10
Model Number: 946 with model MultivariateRegression in generation 7 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 946 in generation 7: MultivariateRegression
Model Number: 947 with model WindowRegression in generation 7 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\experimental\enable_hist_gradient_boosting.py:15: UserWarning:

Since version 1.0, it is not needed to import enable_hist_gradient_boosting anymore. HistGradientBoostingClassifier and HistGradientBoostingRegressor are now stable and can be normally imported from sklearn.ensemble.

Model Number: 948 with model UnobservedComponents in generation 7 of 10
Model Number: 949 with model ARIMA in generation 7 of 10
Model Number: 950 with model UnivariateMotif in generation 7 of 10
Model Number: 951 with model ARIMA in generation 7 of 10
Model Number: 952 with model ETS in generation 7 of 10
Model Number: 953 with model Theta in generation 7 of 10
Model Number: 954 with model Theta in generation 7 of 10
Model Number: 955 with model ARIMA in generation 7 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 955 in generation 7: ARIMA
Model Number: 956 with model GLS in generation 7 of 10
Model Number: 957 with model MetricMotif in generation 7 of 10
Model Number: 958 with model MultivariateRegression in generation 7 of 10
Template Eval Error: ModuleNotFoundError("No module named 'lightgbm'") in model 958 in generation 7: MultivariateRegression
Model Number: 959 with model Theta in generation 7 of 10
Model Number: 960 with model AverageValueNaive in generation 7 of 10
Model Number: 961 with model UnobservedComponents in generation 7 of 10
Template Eval Error: Exception('Transformer RobustScaler failed on fit') in model 961 in generation 7: UnobservedComponents
Model Number: 962 with model ARDL in generation 7 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

Model Number: 963 with model LastValueNaive in generation 7 of 10
Model Number: 964 with model NVAR in generation 7 of 10
Model Number: 965 with model UnivariateMotif in generation 7 of 10
Model Number: 966 with model UnobservedComponents in generation 7 of 10
Model Number: 967 with model ETS in generation 7 of 10
Model Number: 968 with model SectionalMotif in generation 7 of 10
Model Number: 969 with model MultivariateRegression in generation 7 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 969 in generation 7: MultivariateRegression
Model Number: 970 with model SeasonalNaive in generation 7 of 10
Model Number: 971 with model NVAR in generation 7 of 10
Model Number: 972 with model SeasonalNaive in generation 7 of 10
Model Number: 973 with model AverageValueNaive in generation 7 of 10
Model Number: 974 with model ARIMA in generation 7 of 10
Model Number: 975 with model SectionalMotif in generation 7 of 10
Model Number: 976 with model ARIMA in generation 7 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 976 in generation 7: ARIMA
Model Number: 977 with model MultivariateMotif in generation 7 of 10
Model Number: 978 with model Theta in generation 7 of 10
Model Number: 979 with model ConstantNaive in generation 7 of 10
Model Number: 980 with model LastValueNaive in generation 7 of 10
Model Number: 981 with model Theta in generation 7 of 10
Model Number: 982 with model MetricMotif in generation 7 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 982 in generation 7: MetricMotif
Model Number: 983 with model SectionalMotif in generation 7 of 10
Model Number: 984 with model Theta in generation 7 of 10
Model Number: 985 with model UnobservedComponents in generation 7 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor supplied") in model 985 in generation 7: UnobservedComponents
Model Number: 986 with model ConstantNaive in generation 7 of 10
New Generation: 8 of 10
Model Number: 987 with model MetricMotif in generation 8 of 10
Model Number: 988 with model ConstantNaive in generation 8 of 10
Model Number: 989 with model ARIMA in generation 8 of 10
Model Number: 990 with model AverageValueNaive in generation 8 of 10
Model Number: 991 with model MetricMotif in generation 8 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 991 in generation 8: MetricMotif
Model Number: 992 with model GLS in generation 8 of 10
Model Number: 993 with model AverageValueNaive in generation 8 of 10
Model Number: 994 with model UnobservedComponents in generation 8 of 10
Model Number: 995 with model MultivariateMotif in generation 8 of 10
Model Number: 996 with model ARIMA in generation 8 of 10
Model Number: 997 with model ARDL in generation 8 of 10
Model Number: 998 with model NVAR in generation 8 of 10
Model Number: 999 with model NVAR in generation 8 of 10
Model Number: 1000 with model ARDL in generation 8 of 10
Model Number: 1001 with model SectionalMotif in generation 8 of 10
Model Number: 1002 with model MultivariateRegression in generation 8 of 10
Model Number: 1003 with model ConstantNaive in generation 8 of 10
Model Number: 1004 with model SectionalMotif in generation 8 of 10
Model Number: 1005 with model SeasonalNaive in generation 8 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 1005 in generation 8: SeasonalNaive
Model Number: 1006 with model UnivariateRegression in generation 8 of 10
Model Number: 1007 with model ConstantNaive in generation 8 of 10
Model Number: 1008 with model LastValueNaive in generation 8 of 10
Model Number: 1009 with model UnivariateMotif in generation 8 of 10
Model Number: 1010 with model DatepartRegression in generation 8 of 10
Template Eval Error: Exception('Transformer RobustScaler failed on fit') in model 1010 in generation 8: DatepartRegression
Model Number: 1011 with model GLM in generation 8 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

Model Number: 1012 with model ARIMA in generation 8 of 10
Model Number: 1013 with model LastValueNaive in generation 8 of 10
Model Number: 1014 with model LastValueNaive in generation 8 of 10
Model Number: 1015 with model SectionalMotif in generation 8 of 10
Model Number: 1016 with model AverageValueNaive in generation 8 of 10
Model Number: 1017 with model GLS in generation 8 of 10
Model Number: 1018 with model LastValueNaive in generation 8 of 10
Model Number: 1019 with model UnivariateMotif in generation 8 of 10
Model Number: 1020 with model AverageValueNaive in generation 8 of 10
Model Number: 1021 with model UnivariateRegression in generation 8 of 10
Model Number: 1022 with model NVAR in generation 8 of 10
Model Number: 1023 with model NVAR in generation 8 of 10
Model Number: 1024 with model SectionalMotif in generation 8 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.91111e-41): result may not be accurate.

Model Number: 1025 with model DatepartRegression in generation 8 of 10
Template Eval Error: Exception('Transformer BTCD failed on fit') in model 1025 in generation 8: DatepartRegression
Model Number: 1026 with model Theta in generation 8 of 10
Model Number: 1027 with model ConstantNaive in generation 8 of 10
Model Number: 1028 with model MetricMotif in generation 8 of 10
Model Number: 1029 with model NVAR in generation 8 of 10
Model Number: 1030 with model ConstantNaive in generation 8 of 10
Model Number: 1031 with model LastValueNaive in generation 8 of 10
Model Number: 1032 with model AverageValueNaive in generation 8 of 10
Model Number: 1033 with model MetricMotif in generation 8 of 10
Model Number: 1034 with model ConstantNaive in generation 8 of 10
Model Number: 1035 with model ARDL in generation 8 of 10
Model Number: 1036 with model LastValueNaive in generation 8 of 10
Model Number: 1037 with model MultivariateMotif in generation 8 of 10
Model Number: 1038 with model ARDL in generation 8 of 10
Model Number: 1039 with model Theta in generation 8 of 10
Model Number: 1040 with model MultivariateMotif in generation 8 of 10
Model Number: 1041 with model LastValueNaive in generation 8 of 10
Model Number: 1042 with model ETS in generation 8 of 10
Model Number: 1043 with model GLM in generation 8 of 10
Model Number: 1044 with model AverageValueNaive in generation 8 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

Model Number: 1045 with model ARDL in generation 8 of 10
Template Eval Error: Exception('Transformer BTCD failed on fit') in model 1045 in generation 8: ARDL
Model Number: 1046 with model ConstantNaive in generation 8 of 10
Model Number: 1047 with model Theta in generation 8 of 10
Model Number: 1048 with model ETS in generation 8 of 10
Model Number: 1049 with model Theta in generation 8 of 10
Model Number: 1050 with model UnobservedComponents in generation 8 of 10
Model Number: 1051 with model AverageValueNaive in generation 8 of 10
Model Number: 1052 with model ConstantNaive in generation 8 of 10
Model Number: 1053 with model ARIMA in generation 8 of 10
Model Number: 1054 with model ConstantNaive in generation 8 of 10
Model Number: 1055 with model ARIMA in generation 8 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 1055 in generation 8: ARIMA
Model Number: 1056 with model Theta in generation 8 of 10
Model Number: 1057 with model UnivariateMotif in generation 8 of 10
Model Number: 1058 with model MetricMotif in generation 8 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1058 in generation 8: MetricMotif
Model Number: 1059 with model Theta in generation 8 of 10
Model Number: 1060 with model ARIMA in generation 8 of 10
Model Number: 1061 with model NVAR in generation 8 of 10
Model Number: 1062 with model MetricMotif in generation 8 of 10
Model Number: 1063 with model MetricMotif in generation 8 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 1063 in generation 8: MetricMotif
Model Number: 1064 with model NVAR in generation 8 of 10
Model Number: 1065 with model SectionalMotif in generation 8 of 10
Model Number: 1066 with model Theta in generation 8 of 10
Model Number: 1067 with model LastValueNaive in generation 8 of 10
Template Eval Error: Exception('Transformer MinMaxScaler failed on inverse') in model 1067 in generation 8: LastValueNaive
Model Number: 1068 with model ARIMA in generation 8 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 1068 in generation 8: ARIMA
Model Number: 1069 with model AverageValueNaive in generation 8 of 10
Model Number: 1070 with model UnivariateMotif in generation 8 of 10
Model Number: 1071 with model DatepartRegression in generation 8 of 10
Model Number: 1072 with model UnivariateRegression in generation 8 of 10
Model Number: 1073 with model Theta in generation 8 of 10
Model Number: 1074 with model UnobservedComponents in generation 8 of 10
Model Number: 1075 with model ARIMA in generation 8 of 10
Model Number: 1076 with model AverageValueNaive in generation 8 of 10
Model Number: 1077 with model ETS in generation 8 of 10
Model Number: 1078 with model UnobservedComponents in generation 8 of 10
Model Number: 1079 with model ARDL in generation 8 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 1079 in generation 8: ARDL
Model Number: 1080 with model UnobservedComponents in generation 8 of 10
Model Number: 1081 with model SectionalMotif in generation 8 of 10
Model Number: 1082 with model MetricMotif in generation 8 of 10
Model Number: 1083 with model LastValueNaive in generation 8 of 10
Model Number: 1084 with model SeasonalNaive in generation 8 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\decomposition\_pca.py:543: RuntimeWarning:

invalid value encountered in divide

Model Number: 1085 with model DatepartRegression in generation 8 of 10
Template Eval Error: Exception('Transformer BTCD failed on fit') in model 1085 in generation 8: DatepartRegression
Model Number: 1086 with model UnobservedComponents in generation 8 of 10
New Generation: 9 of 10
Model Number: 1087 with model MetricMotif in generation 9 of 10
Model Number: 1088 with model ARIMA in generation 9 of 10
Model Number: 1089 with model SectionalMotif in generation 9 of 10
Model Number: 1090 with model ETS in generation 9 of 10
Model Number: 1091 with model SectionalMotif in generation 9 of 10
Model Number: 1092 with model UnobservedComponents in generation 9 of 10
Model Number: 1093 with model LastValueNaive in generation 9 of 10
Model Number: 1094 with model UnobservedComponents in generation 9 of 10
Model Number: 1095 with model ARIMA in generation 9 of 10
Model Number: 1096 with model LastValueNaive in generation 9 of 10
Model Number: 1097 with model Theta in generation 9 of 10
Model Number: 1098 with model ConstantNaive in generation 9 of 10
Model Number: 1099 with model ARIMA in generation 9 of 10
Model Number: 1100 with model MultivariateMotif in generation 9 of 10
Model Number: 1101 with model ConstantNaive in generation 9 of 10
Model Number: 1102 with model SeasonalNaive in generation 9 of 10
Model Number: 1103 with model LastValueNaive in generation 9 of 10
Model Number: 1104 with model SeasonalNaive in generation 9 of 10
Model Number: 1105 with model NVAR in generation 9 of 10
Model Number: 1106 with model UnivariateMotif in generation 9 of 10
Model Number: 1107 with model UnivariateMotif in generation 9 of 10
Model Number: 1108 with model GLM in generation 9 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

Model Number: 1109 with model MetricMotif in generation 9 of 10
Model Number: 1110 with model SectionalMotif in generation 9 of 10
Model Number: 1111 with model LastValueNaive in generation 9 of 10
Model Number: 1112 with model ARIMA in generation 9 of 10
Model Number: 1113 with model ARDL in generation 9 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1113 in generation 9: ARDL
Model Number: 1114 with model Theta in generation 9 of 10
Model Number: 1115 with model LastValueNaive in generation 9 of 10
Model Number: 1116 with model NVAR in generation 9 of 10
Model Number: 1117 with model WindowRegression in generation 9 of 10
Template Eval Error: ModuleNotFoundError("No module named 'xgboost'") in model 1117 in generation 9: WindowRegression
Model Number: 1118 with model SeasonalNaive in generation 9 of 10
Model Number: 1119 with model NVAR in generation 9 of 10
Model Number: 1120 with model MultivariateRegression in generation 9 of 10
Model Number: 1121 with model AverageValueNaive in generation 9 of 10
Template Eval Error: Exception('Transformer KalmanSmoothing failed on fit') in model 1121 in generation 9: AverageValueNaive
Model Number: 1122 with model UnivariateRegression in generation 9 of 10
Model Number: 1123 with model MetricMotif in generation 9 of 10
Model Number: 1124 with model MultivariateRegression in generation 9 of 10
Model Number: 1125 with model SeasonalNaive in generation 9 of 10
Model Number: 1126 with model GLS in generation 9 of 10
Model Number: 1127 with model SeasonalNaive in generation 9 of 10
Model Number: 1128 with model UnivariateMotif in generation 9 of 10
Model Number: 1129 with model ConstantNaive in generation 9 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 1129 in generation 9: ConstantNaive
Model Number: 1130 with model ARDL in generation 9 of 10
Model Number: 1131 with model MultivariateMotif in generation 9 of 10
Model Number: 1132 with model MetricMotif in generation 9 of 10
Model Number: 1133 with model SeasonalNaive in generation 9 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.52401e-25): result may not be accurate.

Model Number: 1134 with model GLM in generation 9 of 10
Model Number: 1135 with model LastValueNaive in generation 9 of 10
Model Number: 1136 with model ETS in generation 9 of 10
Model Number: 1137 with model Theta in generation 9 of 10
Model Number: 1138 with model WindowRegression in generation 9 of 10
Model Number: 1139 with model SeasonalNaive in generation 9 of 10
Model Number: 1140 with model ARIMA in generation 9 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 1140 in generation 9: ARIMA
Model Number: 1141 with model ARDL in generation 9 of 10
Model Number: 1142 with model ARIMA in generation 9 of 10
Model Number: 1143 with model ARDL in generation 9 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 1143 in generation 9: ARDL
Model Number: 1144 with model Theta in generation 9 of 10
Model Number: 1145 with model NVAR in generation 9 of 10
Model Number: 1146 with model NVAR in generation 9 of 10
Model Number: 1147 with model MultivariateMotif in generation 9 of 10
Model Number: 1148 with model AverageValueNaive in generation 9 of 10
Model Number: 1149 with model SeasonalNaive in generation 9 of 10
Model Number: 1150 with model UnivariateRegression in generation 9 of 10
Model Number: 1151 with model ConstantNaive in generation 9 of 10
Model Number: 1152 with model ARDL in generation 9 of 10
Model Number: 1153 with model UnivariateMotif in generation 9 of 10
Model Number: 1154 with model Theta in generation 9 of 10
Model Number: 1155 with model UnobservedComponents in generation 9 of 10
Model Number: 1156 with model ETS in generation 9 of 10
Model Number: 1157 with model Theta in generation 9 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\decomposition\_fastica.py:576: UserWarning:

Ignoring n_components with whiten=False.

Model Number: 1158 with model DatepartRegression in generation 9 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor passed") in model 1158 in generation 9: DatepartRegression
Model Number: 1159 with model UnivariateMotif in generation 9 of 10
Model Number: 1160 with model Theta in generation 9 of 10
Model Number: 1161 with model ConstantNaive in generation 9 of 10
Model Number: 1162 with model AverageValueNaive in generation 9 of 10
Model Number: 1163 with model UnobservedComponents in generation 9 of 10
Model Number: 1164 with model UnobservedComponents in generation 9 of 10
Template Eval Error: Exception('Transformer Cointegration failed on fit') in model 1164 in generation 9: UnobservedComponents
Model Number: 1165 with model UnivariateMotif in generation 9 of 10
Model Number: 1166 with model LastValueNaive in generation 9 of 10
Model Number: 1167 with model UnivariateMotif in generation 9 of 10
Model Number: 1168 with model ARDL in generation 9 of 10
Template Eval Error: ValueError("regression_type='User' but future_regressor not supplied") in model 1168 in generation 9: ARDL
Model Number: 1169 with model DatepartRegression in generation 9 of 10
Template Eval Error: ValueError('Model DatepartRegression returned NaN for one or more series. fail_on_forecast_nan=True') in model 1169 in generation 9: DatepartRegression
Model Number: 1170 with model MultivariateMotif in generation 9 of 10
Model Number: 1171 with model LastValueNaive in generation 9 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_regression.py:500: UserWarning:

One or more samples have no neighbors within specified radius; predicting NaN.

Model Number: 1172 with model ARIMA in generation 9 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 1172 in generation 9: ARIMA
Model Number: 1173 with model SeasonalNaive in generation 9 of 10
Model Number: 1174 with model Theta in generation 9 of 10
Model Number: 1175 with model ARDL in generation 9 of 10
Model Number: 1176 with model NVAR in generation 9 of 10
Model Number: 1177 with model ARIMA in generation 9 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 1177 in generation 9: ARIMA
Model Number: 1178 with model UnobservedComponents in generation 9 of 10
Model Number: 1179 with model ARIMA in generation 9 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

Model Number: 1180 with model MultivariateMotif in generation 9 of 10
Template Eval Error: Exception('Transformer AlignLastValue failed on inverse') in model 1180 in generation 9: MultivariateMotif
Model Number: 1181 with model LastValueNaive in generation 9 of 10
Model Number: 1182 with model NVAR in generation 9 of 10
Model Number: 1183 with model ARIMA in generation 9 of 10
Model Number: 1184 with model ETS in generation 9 of 10
Template Eval Error: Exception('Transformer MinMaxScaler failed on inverse') in model 1184 in generation 9: ETS
Model Number: 1185 with model GLM in generation 9 of 10
Model Number: 1186 with model ARIMA in generation 9 of 10
New Generation: 10 of 10
Model Number: 1187 with model SeasonalNaive in generation 10 of 10
Model Number: 1188 with model WindowRegression in generation 10 of 10
Template Eval Error: ValueError("regression_type='User' but no future_regressor passed") in model 1188 in generation 10: WindowRegression
Model Number: 1189 with model LastValueNaive in generation 10 of 10
Model Number: 1190 with model AverageValueNaive in generation 10 of 10
Model Number: 1191 with model NVAR in generation 10 of 10
Model Number: 1192 with model SeasonalNaive in generation 10 of 10
Model Number: 1193 with model UnobservedComponents in generation 10 of 10
Model Number: 1194 with model UnivariateMotif in generation 10 of 10
Model Number: 1195 with model Theta in generation 10 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

Template Eval Error: Exception('Transformer ReplaceConstant failed on inverse') in model 1195 in generation 10: Theta
Model Number: 1196 with model ARIMA in generation 10 of 10
Model Number: 1197 with model LastValueNaive in generation 10 of 10
Model Number: 1198 with model ConstantNaive in generation 10 of 10
Model Number: 1199 with model NVAR in generation 10 of 10
Model Number: 1200 with model ARIMA in generation 10 of 10
Model Number: 1201 with model ConstantNaive in generation 10 of 10
Model Number: 1202 with model ARIMA in generation 10 of 10
Model Number: 1203 with model NVAR in generation 10 of 10
Model Number: 1204 with model SeasonalNaive in generation 10 of 10
Model Number: 1205 with model UnobservedComponents in generation 10 of 10
Model Number: 1206 with model AverageValueNaive in generation 10 of 10
Model Number: 1207 with model ARDL in generation 10 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\autots\tools\percentile.py:47: RuntimeWarning:

All-NaN slice encountered

Model Number: 1208 with model AverageValueNaive in generation 10 of 10
Template Eval Error: Exception('Transformer FastICA failed on fit') in model 1208 in generation 10: AverageValueNaive
Model Number: 1209 with model DatepartRegression in generation 10 of 10
Model Number: 1210 with model GLS in generation 10 of 10
Model Number: 1211 with model ARIMA in generation 10 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.52401e-25): result may not be accurate.

Model Number: 1212 with model Theta in generation 10 of 10
Model Number: 1213 with model MetricMotif in generation 10 of 10
Model Number: 1214 with model ARIMA in generation 10 of 10
Template Eval Error: Exception('Transformer ScipyFilter failed on fit') in model 1214 in generation 10: ARIMA
Model Number: 1215 with model NVAR in generation 10 of 10
Model Number: 1216 with model MetricMotif in generation 10 of 10
Model Number: 1217 with model UnivariateRegression in generation 10 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.9111e-41): result may not be accurate.

Model Number: 1218 with model Theta in generation 10 of 10
Model Number: 1219 with model Theta in generation 10 of 10
Model Number: 1220 with model MultivariateMotif in generation 10 of 10
Model Number: 1221 with model ConstantNaive in generation 10 of 10
Model Number: 1222 with model ConstantNaive in generation 10 of 10
Model Number: 1223 with model ARDL in generation 10 of 10
Model Number: 1224 with model UnivariateMotif in generation 10 of 10
Model Number: 1225 with model SectionalMotif in generation 10 of 10
Template Eval Error: ValueError("regression_type=='User' but no future_regressor supplied") in model 1225 in generation 10: SectionalMotif
Model Number: 1226 with model ARIMA in generation 10 of 10
Model Number: 1227 with model LastValueNaive in generation 10 of 10
Model Number: 1228 with model UnivariateMotif in generation 10 of 10
Model Number: 1229 with model ARDL in generation 10 of 10
Model Number: 1230 with model SectionalMotif in generation 10 of 10
Template Eval Error: ValueError("regression_type=='User' but no future_regressor supplied") in model 1230 in generation 10: SectionalMotif
Model Number: 1231 with model AverageValueNaive in generation 10 of 10
Model Number: 1232 with model ARDL in generation 10 of 10
Model Number: 1233 with model UnivariateMotif in generation 10 of 10
Model Number: 1234 with model SeasonalNaive in generation 10 of 10
Model Number: 1235 with model MetricMotif in generation 10 of 10
Model Number: 1236 with model ConstantNaive in generation 10 of 10
Model Number: 1237 with model AverageValueNaive in generation 10 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 1237 in generation 10: AverageValueNaive
Model Number: 1238 with model ConstantNaive in generation 10 of 10
Model Number: 1239 with model MetricMotif in generation 10 of 10
Model Number: 1240 with model UnobservedComponents in generation 10 of 10
Model Number: 1241 with model AverageValueNaive in generation 10 of 10
Model Number: 1242 with model AverageValueNaive in generation 10 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 1242 in generation 10: AverageValueNaive
Model Number: 1243 with model AverageValueNaive in generation 10 of 10
Model Number: 1244 with model ConstantNaive in generation 10 of 10
Model Number: 1245 with model LastValueNaive in generation 10 of 10
Model Number: 1246 with model UnivariateMotif in generation 10 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\autots\tools\percentile.py:47: RuntimeWarning:

All-NaN slice encountered

Model Number: 1247 with model SeasonalNaive in generation 10 of 10
Model Number: 1248 with model Theta in generation 10 of 10
Model Number: 1249 with model SeasonalNaive in generation 10 of 10
Model Number: 1250 with model AverageValueNaive in generation 10 of 10
Model Number: 1251 with model ARIMA in generation 10 of 10
Model Number: 1252 with model NVAR in generation 10 of 10
Model Number: 1253 with model ARDL in generation 10 of 10
Model Number: 1254 with model ETS in generation 10 of 10
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.52401e-25): result may not be accurate.

Model Number: 1255 with model Theta in generation 10 of 10
Model Number: 1256 with model ARIMA in generation 10 of 10
Model Number: 1257 with model NVAR in generation 10 of 10
Model Number: 1258 with model LastValueNaive in generation 10 of 10
Model Number: 1259 with model Theta in generation 10 of 10
Template Eval Error: Exception('Transformer ReplaceConstant failed on fit') in model 1259 in generation 10: Theta
Model Number: 1260 with model MetricMotif in generation 10 of 10
Model Number: 1261 with model NVAR in generation 10 of 10
Model Number: 1262 with model Ensemble in generation 11 of Ensembles
Model Number: 1263 with model Ensemble in generation 11 of Ensembles
Model Number: 1264 with model Ensemble in generation 11 of Ensembles
Model Number: 1265 with model Ensemble in generation 11 of Ensembles
Model Number: 1266 with model Ensemble in generation 11 of Ensembles
Model Number: 1267 with model Ensemble in generation 11 of Ensembles
Model Number: 1268 with model Ensemble in generation 11 of Ensembles
Model Number: 1269 with model Ensemble in generation 11 of Ensembles
Validation Round: 1
Model Number: 1 of 188 with model Ensemble for Validation 1
📈 1 - Ensemble with avg smape 8.85: 
Model Number: 2 of 188 with model Ensemble for Validation 1
📈 2 - Ensemble with avg smape 8.8: 
Model Number: 3 of 188 with model Ensemble for Validation 1
3 - Ensemble with avg smape 8.8: 
Model Number: 4 of 188 with model Ensemble for Validation 1
4 - Ensemble with avg smape 10.16: 
Model Number: 5 of 188 with model Ensemble for Validation 1
5 - Ensemble with avg smape 9.92: 
Model Number: 6 of 188 with model Ensemble for Validation 1
6 - Ensemble with avg smape 9.86: 
Model Number: 7 of 188 with model ARIMA for Validation 1
7 - ARIMA with avg smape 9.83: 
Model Number: 8 of 188 with model Theta for Validation 1
8 - Theta with avg smape 9.95: 
Model Number: 9 of 188 with model Theta for Validation 1
9 - Theta with avg smape 9.97: 
Model Number: 10 of 188 with model Theta for Validation 1
10 - Theta with avg smape 9.98: 
Model Number: 11 of 188 with model Ensemble for Validation 1
11 - Ensemble with avg smape 9.68: 
Model Number: 12 of 188 with model UnivariateMotif for Validation 1
📈 12 - UnivariateMotif with avg smape 6.65: 
Model Number: 13 of 188 with model UnivariateMotif for Validation 1
13 - UnivariateMotif with avg smape 7.54: 
Model Number: 14 of 188 with model UnivariateMotif for Validation 1
14 - UnivariateMotif with avg smape 8.16: 
Model Number: 15 of 188 with model Theta for Validation 1
15 - Theta with avg smape 9.16: 
Model Number: 16 of 188 with model ARDL for Validation 1
16 - ARDL with avg smape 11.61: 
Model Number: 17 of 188 with model ARIMA for Validation 1
17 - ARIMA with avg smape 9.3: 
Model Number: 18 of 188 with model Theta for Validation 1
18 - Theta with avg smape 9.62: 
Model Number: 19 of 188 with model ARIMA for Validation 1
19 - ARIMA with avg smape 9.91: 
Model Number: 20 of 188 with model ARIMA for Validation 1
20 - ARIMA with avg smape 11.4: 
Model Number: 21 of 188 with model ARIMA for Validation 1
21 - ARIMA with avg smape 8.8: 
Model Number: 22 of 188 with model Theta for Validation 1
22 - Theta with avg smape 9.63: 
Model Number: 23 of 188 with model Theta for Validation 1
23 - Theta with avg smape 9.63: 
Model Number: 24 of 188 with model NVAR for Validation 1
24 - NVAR with avg smape 11.89: 
Model Number: 25 of 188 with model Theta for Validation 1
25 - Theta with avg smape 9.63: 
Model Number: 26 of 188 with model NVAR for Validation 1
26 - NVAR with avg smape 11.05: 
Model Number: 27 of 188 with model AverageValueNaive for Validation 1
27 - AverageValueNaive with avg smape 9.55: 
Model Number: 28 of 188 with model NVAR for Validation 1
28 - NVAR with avg smape 11.04: 
Model Number: 29 of 188 with model ARIMA for Validation 1
29 - ARIMA with avg smape 7.07: 
Model Number: 30 of 188 with model Theta for Validation 1
30 - Theta with avg smape 9.6: 
Model Number: 31 of 188 with model NVAR for Validation 1
31 - NVAR with avg smape 10.32: 
Model Number: 32 of 188 with model NVAR for Validation 1
32 - NVAR with avg smape 10.32: 
Model Number: 33 of 188 with model NVAR for Validation 1
33 - NVAR with avg smape 10.32: 
Model Number: 34 of 188 with model NVAR for Validation 1
34 - NVAR with avg smape 10.32: 
Model Number: 35 of 188 with model NVAR for Validation 1
35 - NVAR with avg smape 10.32: 
Model Number: 36 of 188 with model NVAR for Validation 1
36 - NVAR with avg smape 10.32: 
Model Number: 37 of 188 with model AverageValueNaive for Validation 1
37 - AverageValueNaive with avg smape 9.55: 
Model Number: 38 of 188 with model ARIMA for Validation 1
38 - ARIMA with avg smape 8.21: 
Model Number: 39 of 188 with model AverageValueNaive for Validation 1
39 - AverageValueNaive with avg smape 9.55: 
Model Number: 40 of 188 with model ARIMA for Validation 1
40 - ARIMA with avg smape 9.29: 
Model Number: 41 of 188 with model AverageValueNaive for Validation 1
41 - AverageValueNaive with avg smape 9.55: 
Model Number: 42 of 188 with model AverageValueNaive for Validation 1
42 - AverageValueNaive with avg smape 9.55: 
Model Number: 43 of 188 with model SeasonalNaive for Validation 1
43 - SeasonalNaive with avg smape 9.88: 
Model Number: 44 of 188 with model ARIMA for Validation 1
44 - ARIMA with avg smape 10.03: 
Model Number: 45 of 188 with model SeasonalNaive for Validation 1
45 - SeasonalNaive with avg smape 9.53: 
Model Number: 46 of 188 with model SectionalMotif for Validation 1
46 - SectionalMotif with avg smape 11.0: 
Model Number: 47 of 188 with model SeasonalNaive for Validation 1
47 - SeasonalNaive with avg smape 9.59: 
Model Number: 48 of 188 with model AverageValueNaive for Validation 1
48 - AverageValueNaive with avg smape 9.55: 
Model Number: 49 of 188 with model SectionalMotif for Validation 1
49 - SectionalMotif with avg smape 9.28: 
Model Number: 50 of 188 with model LastValueNaive for Validation 1
50 - LastValueNaive with avg smape 12.95: 
Model Number: 51 of 188 with model LastValueNaive for Validation 1
51 - LastValueNaive with avg smape 12.95: 
Model Number: 52 of 188 with model UnivariateMotif for Validation 1
52 - UnivariateMotif with avg smape 6.73: 
Model Number: 53 of 188 with model ConstantNaive for Validation 1
53 - ConstantNaive with avg smape 10.28: 
Model Number: 54 of 188 with model ConstantNaive for Validation 1
54 - ConstantNaive with avg smape 10.28: 
Model Number: 55 of 188 with model LastValueNaive for Validation 1
55 - LastValueNaive with avg smape 13.15: 
Model Number: 56 of 188 with model ConstantNaive for Validation 1
56 - ConstantNaive with avg smape 10.58: 
Model Number: 57 of 188 with model ConstantNaive for Validation 1
57 - ConstantNaive with avg smape 10.58: 
Model Number: 58 of 188 with model ConstantNaive for Validation 1
58 - ConstantNaive with avg smape 10.58: 
Model Number: 59 of 188 with model ConstantNaive for Validation 1
59 - ConstantNaive with avg smape 10.58: 
Model Number: 60 of 188 with model ConstantNaive for Validation 1
60 - ConstantNaive with avg smape 10.58: 
Model Number: 61 of 188 with model LastValueNaive for Validation 1
61 - LastValueNaive with avg smape 13.32: 
Model Number: 62 of 188 with model LastValueNaive for Validation 1
62 - LastValueNaive with avg smape 13.35: 
Model Number: 63 of 188 with model ARDL for Validation 1
63 - ARDL with avg smape 11.79: 
Model Number: 64 of 188 with model LastValueNaive for Validation 1
64 - LastValueNaive with avg smape 13.94: 
Model Number: 65 of 188 with model UnivariateMotif for Validation 1
65 - UnivariateMotif with avg smape 8.22: 
Model Number: 66 of 188 with model ConstantNaive for Validation 1
66 - ConstantNaive with avg smape 8.56: 
Model Number: 67 of 188 with model ConstantNaive for Validation 1
67 - ConstantNaive with avg smape 9.73: 
Model Number: 68 of 188 with model LastValueNaive for Validation 1
68 - LastValueNaive with avg smape 13.12: 
Model Number: 69 of 188 with model LastValueNaive for Validation 1
69 - LastValueNaive with avg smape 13.12: 
Model Number: 70 of 188 with model SeasonalNaive for Validation 1
70 - SeasonalNaive with avg smape 9.54: 
Model Number: 71 of 188 with model LastValueNaive for Validation 1
71 - LastValueNaive with avg smape 13.12: 
Model Number: 72 of 188 with model ARDL for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

72 - ARDL with avg smape 12.04: 
Model Number: 73 of 188 with model ARDL for Validation 1
73 - ARDL with avg smape 11.56: 
Model Number: 74 of 188 with model AverageValueNaive for Validation 1
📈 74 - AverageValueNaive with avg smape 6.06: 
Model Number: 75 of 188 with model AverageValueNaive for Validation 1
75 - AverageValueNaive with avg smape 9.55: 
Model Number: 76 of 188 with model AverageValueNaive for Validation 1
76 - AverageValueNaive with avg smape 9.55: 
Model Number: 77 of 188 with model SeasonalNaive for Validation 1
77 - SeasonalNaive with avg smape 8.88: 
Model Number: 78 of 188 with model ARDL for Validation 1
78 - ARDL with avg smape 11.3: 
Model Number: 79 of 188 with model SectionalMotif for Validation 1
79 - SectionalMotif with avg smape 7.21: 
Model Number: 80 of 188 with model MetricMotif for Validation 1
80 - MetricMotif with avg smape 10.92: 
Model Number: 81 of 188 with model ARDL for Validation 1
81 - ARDL with avg smape 11.64: 
Model Number: 82 of 188 with model ARDL for Validation 1
82 - ARDL with avg smape 11.64: 
Model Number: 83 of 188 with model ARDL for Validation 1
83 - ARDL with avg smape 11.64: 
Model Number: 84 of 188 with model ARDL for Validation 1
84 - ARDL with avg smape 11.64: 
Model Number: 85 of 188 with model MetricMotif for Validation 1
85 - MetricMotif with avg smape 10.84: 
Model Number: 86 of 188 with model MetricMotif for Validation 1
86 - MetricMotif with avg smape 16.39: 
Model Number: 87 of 188 with model MetricMotif for Validation 1
87 - MetricMotif with avg smape 9.34: 
Model Number: 88 of 188 with model UnivariateMotif for Validation 1
88 - UnivariateMotif with avg smape 17.61: 
Model Number: 89 of 188 with model UnivariateMotif for Validation 1
89 - UnivariateMotif with avg smape 17.61: 
Model Number: 90 of 188 with model MetricMotif for Validation 1
90 - MetricMotif with avg smape 11.02: 
Model Number: 91 of 188 with model UnivariateMotif for Validation 1
91 - UnivariateMotif with avg smape 7.24: 
Model Number: 92 of 188 with model MultivariateMotif for Validation 1
92 - MultivariateMotif with avg smape 10.25: 
Model Number: 93 of 188 with model MetricMotif for Validation 1
93 - MetricMotif with avg smape 11.75: 
Model Number: 94 of 188 with model MultivariateMotif for Validation 1
94 - MultivariateMotif with avg smape 10.26: 
Model Number: 95 of 188 with model MetricMotif for Validation 1
95 - MetricMotif with avg smape 10.5: 
Model Number: 96 of 188 with model ETS for Validation 1
96 - ETS with avg smape 9.55: 
Model Number: 97 of 188 with model UnivariateMotif for Validation 1
97 - UnivariateMotif with avg smape 28.64: 
Model Number: 98 of 188 with model MetricMotif for Validation 1
98 - MetricMotif with avg smape 12.67: 
Model Number: 99 of 188 with model WindowRegression for Validation 1
99 - WindowRegression with avg smape 9.95: 
Model Number: 100 of 188 with model MetricMotif for Validation 1
100 - MetricMotif with avg smape 12.2: 
Model Number: 101 of 188 with model UnobservedComponents for Validation 1
101 - UnobservedComponents with avg smape 6.39: 
Model Number: 102 of 188 with model UnobservedComponents for Validation 1
102 - UnobservedComponents with avg smape 12.92: 
Model Number: 103 of 188 with model UnobservedComponents for Validation 1
103 - UnobservedComponents with avg smape 9.58: 
Model Number: 104 of 188 with model GLS for Validation 1
104 - GLS with avg smape 13.09: 
Model Number: 105 of 188 with model ETS for Validation 1
105 - ETS with avg smape 9.55: 
Model Number: 106 of 188 with model SeasonalNaive for Validation 1
106 - SeasonalNaive with avg smape 13.33: 
Model Number: 107 of 188 with model SeasonalNaive for Validation 1
107 - SeasonalNaive with avg smape 13.38: 
Model Number: 108 of 188 with model MultivariateMotif for Validation 1
108 - MultivariateMotif with avg smape 14.06: 
Model Number: 109 of 188 with model MultivariateMotif for Validation 1
109 - MultivariateMotif with avg smape 14.06: 
Model Number: 110 of 188 with model ETS for Validation 1
110 - ETS with avg smape 9.55: 
Model Number: 111 of 188 with model GLS for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\decomposition\_fastica.py:576: UserWarning:

Ignoring n_components with whiten=False.

111 - GLS with avg smape 13.14: 
Model Number: 112 of 188 with model SeasonalNaive for Validation 1
112 - SeasonalNaive with avg smape 13.37: 
Model Number: 113 of 188 with model SeasonalNaive for Validation 1
113 - SeasonalNaive with avg smape 13.37: 
Model Number: 114 of 188 with model UnobservedComponents for Validation 1
114 - UnobservedComponents with avg smape 9.55: 
Model Number: 115 of 188 with model UnobservedComponents for Validation 1
📈 115 - UnobservedComponents with avg smape 5.91: 
Model Number: 116 of 188 with model ETS for Validation 1
116 - ETS with avg smape 9.55: 
Model Number: 117 of 188 with model ETS for Validation 1
117 - ETS with avg smape 9.56: 
Model Number: 118 of 188 with model UnobservedComponents for Validation 1
118 - UnobservedComponents with avg smape 10.5: 
Model Number: 119 of 188 with model UnobservedComponents for Validation 1
📈 119 - UnobservedComponents with avg smape 5.69: 
Model Number: 120 of 188 with model UnobservedComponents for Validation 1
120 - UnobservedComponents with avg smape 9.56: 
Model Number: 121 of 188 with model UnobservedComponents for Validation 1
121 - UnobservedComponents with avg smape 9.56: 
Model Number: 122 of 188 with model UnivariateRegression for Validation 1
122 - UnivariateRegression with avg smape 9.4: 
Model Number: 123 of 188 with model DatepartRegression for Validation 1
123 - DatepartRegression with avg smape 9.47: 
Model Number: 124 of 188 with model GLM for Validation 1
124 - GLM with avg smape 9.56: 
Model Number: 125 of 188 with model DatepartRegression for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

125 - DatepartRegression with avg smape 14.64: 
Model Number: 126 of 188 with model GLM for Validation 1
126 - GLM with avg smape 9.56: 
Model Number: 127 of 188 with model ETS for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

127 - ETS with avg smape 9.55: 
Model Number: 128 of 188 with model ETS for Validation 1
128 - ETS with avg smape 9.55: 
Model Number: 129 of 188 with model MultivariateRegression for Validation 1
129 - MultivariateRegression with avg smape 9.71: 
Model Number: 130 of 188 with model ETS for Validation 1
130 - ETS with avg smape 9.55: 
Model Number: 131 of 188 with model ETS for Validation 1
131 - ETS with avg smape 9.55: 
Model Number: 132 of 188 with model DatepartRegression for Validation 1
132 - DatepartRegression with avg smape 10.06: 
Model Number: 133 of 188 with model Ensemble for Validation 1
133 - Ensemble with avg smape 15.57: 
Model Number: 134 of 188 with model MultivariateRegression for Validation 1
134 - MultivariateRegression with avg smape 9.61: 
Model Number: 135 of 188 with model GLM for Validation 1
135 - GLM with avg smape 9.55: 
Model Number: 136 of 188 with model SectionalMotif for Validation 1
136 - SectionalMotif with avg smape 6.03: 
Model Number: 137 of 188 with model GLM for Validation 1
137 - GLM with avg smape 21.19: 
Model Number: 138 of 188 with model SectionalMotif for Validation 1
138 - SectionalMotif with avg smape 11.53: 
Model Number: 139 of 188 with model SectionalMotif for Validation 1
139 - SectionalMotif with avg smape 6.63: 
Model Number: 140 of 188 with model GLM for Validation 1
140 - GLM with avg smape 19.47: 
Model Number: 141 of 188 with model GLS for Validation 1
141 - GLS with avg smape 9.58: 
Model Number: 142 of 188 with model WindowRegression for Validation 1
142 - WindowRegression with avg smape 10.74: 
Model Number: 143 of 188 with model DatepartRegression for Validation 1
143 - DatepartRegression with avg smape 10.76: 
Model Number: 144 of 188 with model DatepartRegression for Validation 1
144 - DatepartRegression with avg smape 10.77: 
Model Number: 145 of 188 with model GLM for Validation 1
145 - GLM with avg smape 9.55: 
Model Number: 146 of 188 with model GLS for Validation 1
146 - GLS with avg smape 9.5: 
Model Number: 147 of 188 with model GLS for Validation 1
147 - GLS with avg smape 9.55: 
Model Number: 148 of 188 with model GLM for Validation 1
148 - GLM with avg smape 9.55: 
Model Number: 149 of 188 with model GLM for Validation 1
149 - GLM with avg smape 21.33: 
Model Number: 150 of 188 with model GLM for Validation 1
150 - GLM with avg smape 9.61: 
Model Number: 151 of 188 with model GLS for Validation 1
151 - GLS with avg smape 9.53: 
Model Number: 152 of 188 with model DatepartRegression for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\generalized_linear_model.py:307: DomainWarning:

The InversePower link function does not respect the domain of the Gamma family.

152 - DatepartRegression with avg smape 10.51: 
Model Number: 153 of 188 with model GLS for Validation 1
153 - GLS with avg smape 9.55: 
Model Number: 154 of 188 with model DatepartRegression for Validation 1
154 - DatepartRegression with avg smape 10.52: 
Model Number: 155 of 188 with model GLS for Validation 1
155 - GLS with avg smape 9.55: 
Model Number: 156 of 188 with model DatepartRegression for Validation 1
156 - DatepartRegression with avg smape 9.55: 
Model Number: 157 of 188 with model UnivariateRegression for Validation 1
157 - UnivariateRegression with avg smape 6.74: 
Model Number: 158 of 188 with model DatepartRegression for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=2.00701e-41): result may not be accurate.

158 - DatepartRegression with avg smape 9.91: 
Model Number: 159 of 188 with model UnivariateRegression for Validation 1
📈 159 - UnivariateRegression with avg smape 2.82: 
Model Number: 160 of 188 with model GLS for Validation 1
160 - GLS with avg smape 6.3: 
Model Number: 161 of 188 with model MultivariateRegression for Validation 1
161 - MultivariateRegression with avg smape 11.49: 
Model Number: 162 of 188 with model SectionalMotif for Validation 1
162 - SectionalMotif with avg smape 6.86: 
Model Number: 163 of 188 with model UnivariateRegression for Validation 1
163 - UnivariateRegression with avg smape 6.39: 
Model Number: 164 of 188 with model MultivariateRegression for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=2.00701e-41): result may not be accurate.

164 - MultivariateRegression with avg smape 14.01: 
Model Number: 165 of 188 with model UnivariateRegression for Validation 1
165 - UnivariateRegression with avg smape 11.87: 
Model Number: 166 of 188 with model WindowRegression for Validation 1
166 - WindowRegression with avg smape 14.5: 
Model Number: 167 of 188 with model MultivariateRegression for Validation 1
167 - MultivariateRegression with avg smape 7.24: 
Model Number: 168 of 188 with model MultivariateMotif for Validation 1
168 - MultivariateMotif with avg smape 4.16: 
Model Number: 169 of 188 with model MultivariateRegression for Validation 1
169 - MultivariateRegression with avg smape 4.74: 
Model Number: 170 of 188 with model UnivariateRegression for Validation 1
170 - UnivariateRegression with avg smape 9.63: 
Model Number: 171 of 188 with model UnivariateRegression for Validation 1
171 - UnivariateRegression with avg smape 9.51: 
Model Number: 172 of 188 with model UnivariateRegression for Validation 1
172 - UnivariateRegression with avg smape 9.51: 
Model Number: 173 of 188 with model UnivariateRegression for Validation 1
173 - UnivariateRegression with avg smape 12.21: 
Model Number: 174 of 188 with model MultivariateMotif for Validation 1
174 - MultivariateMotif with avg smape 21.26: 
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.57317e-25): result may not be accurate.

Model Number: 175 of 188 with model MultivariateMotif for Validation 1
175 - MultivariateMotif with avg smape 5.82: 
Model Number: 176 of 188 with model SectionalMotif for Validation 1
176 - SectionalMotif with avg smape 9.38: 
Model Number: 177 of 188 with model MultivariateMotif for Validation 1
177 - MultivariateMotif with avg smape 16.92: 
Model Number: 178 of 188 with model MultivariateMotif for Validation 1
178 - MultivariateMotif with avg smape 32.0: 
Model Number: 179 of 188 with model SectionalMotif for Validation 1
179 - SectionalMotif with avg smape 7.47: 
Model Number: 180 of 188 with model MultivariateRegression for Validation 1
180 - MultivariateRegression with avg smape 7.83: 
Model Number: 181 of 188 with model MultivariateRegression for Validation 1
181 - MultivariateRegression with avg smape 6.35: 
Model Number: 182 of 188 with model WindowRegression for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

182 - WindowRegression with avg smape 12.69: 
Model Number: 183 of 188 with model WindowRegression for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

183 - WindowRegression with avg smape 12.62: 
Model Number: 184 of 188 with model MultivariateRegression for Validation 1
184 - MultivariateRegression with avg smape 8.22: 
Model Number: 185 of 188 with model WindowRegression for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

185 - WindowRegression with avg smape 23.58: 
Model Number: 186 of 188 with model WindowRegression for Validation 1
186 - WindowRegression with avg smape 8.22: 
Model Number: 187 of 188 with model WindowRegression for Validation 1
187 - WindowRegression with avg smape 16.78: 
Model Number: 188 of 188 with model WindowRegression for Validation 1
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.59228e-25): result may not be accurate.

188 - WindowRegression with avg smape 26.05: 
Validation Round: 2
Model Number: 1 of 188 with model Ensemble for Validation 2
📈 1 - Ensemble with avg smape 16.44: 
Model Number: 2 of 188 with model Ensemble for Validation 2
2 - Ensemble with avg smape 16.51: 
Model Number: 3 of 188 with model Ensemble for Validation 2
3 - Ensemble with avg smape 16.51: 
Model Number: 4 of 188 with model Ensemble for Validation 2
4 - Ensemble with avg smape 17.46: 
Model Number: 5 of 188 with model Ensemble for Validation 2
📈 5 - Ensemble with avg smape 15.43: 
Model Number: 6 of 188 with model Ensemble for Validation 2
6 - Ensemble with avg smape 15.58: 
Model Number: 7 of 188 with model ARIMA for Validation 2
📈 7 - ARIMA with avg smape 15.15: 
Model Number: 8 of 188 with model Theta for Validation 2
8 - Theta with avg smape 15.65: 
Model Number: 9 of 188 with model Theta for Validation 2
9 - Theta with avg smape 15.49: 
Model Number: 10 of 188 with model Theta for Validation 2
10 - Theta with avg smape 15.67: 
Model Number: 11 of 188 with model Ensemble for Validation 2
11 - Ensemble with avg smape 19.58: 
Model Number: 12 of 188 with model UnivariateMotif for Validation 2
12 - UnivariateMotif with avg smape 19.01: 
Model Number: 13 of 188 with model UnivariateMotif for Validation 2
📈 13 - UnivariateMotif with avg smape 14.58: 
Model Number: 14 of 188 with model UnivariateMotif for Validation 2
14 - UnivariateMotif with avg smape 21.97: 
Model Number: 15 of 188 with model Theta for Validation 2
15 - Theta with avg smape 16.07: 
Model Number: 16 of 188 with model ARDL for Validation 2
16 - ARDL with avg smape 26.35: 
Model Number: 17 of 188 with model ARIMA for Validation 2
17 - ARIMA with avg smape 20.82: 
Model Number: 18 of 188 with model Theta for Validation 2
18 - Theta with avg smape 19.55: 
Model Number: 19 of 188 with model ARIMA for Validation 2
19 - ARIMA with avg smape 20.72: 
Model Number: 20 of 188 with model ARIMA for Validation 2
20 - ARIMA with avg smape 17.44: 
Model Number: 21 of 188 with model ARIMA for Validation 2
21 - ARIMA with avg smape 21.36: 
Model Number: 22 of 188 with model Theta for Validation 2
22 - Theta with avg smape 19.45: 
Model Number: 23 of 188 with model Theta for Validation 2
23 - Theta with avg smape 19.47: 
Model Number: 24 of 188 with model NVAR for Validation 2
24 - NVAR with avg smape 19.81: 
Model Number: 25 of 188 with model Theta for Validation 2
25 - Theta with avg smape 19.46: 
Model Number: 26 of 188 with model NVAR for Validation 2
26 - NVAR with avg smape 16.87: 
Model Number: 27 of 188 with model AverageValueNaive for Validation 2
27 - AverageValueNaive with avg smape 19.12: 
Model Number: 28 of 188 with model NVAR for Validation 2
28 - NVAR with avg smape 19.98: 
Model Number: 29 of 188 with model ARIMA for Validation 2
29 - ARIMA with avg smape 15.91: 
Model Number: 30 of 188 with model Theta for Validation 2
30 - Theta with avg smape 19.19: 
Model Number: 31 of 188 with model NVAR for Validation 2
31 - NVAR with avg smape 20.62: 
Model Number: 32 of 188 with model NVAR for Validation 2
32 - NVAR with avg smape 20.62: 
Model Number: 33 of 188 with model NVAR for Validation 2
33 - NVAR with avg smape 20.61: 
Model Number: 34 of 188 with model NVAR for Validation 2
34 - NVAR with avg smape 20.61: 
Model Number: 35 of 188 with model NVAR for Validation 2
35 - NVAR with avg smape 20.61: 
Model Number: 36 of 188 with model NVAR for Validation 2
36 - NVAR with avg smape 20.61: 
Model Number: 37 of 188 with model AverageValueNaive for Validation 2
37 - AverageValueNaive with avg smape 19.12: 
Model Number: 38 of 188 with model ARIMA for Validation 2
📈 38 - ARIMA with avg smape 14.55: 
Model Number: 39 of 188 with model AverageValueNaive for Validation 2
39 - AverageValueNaive with avg smape 19.12: 
Model Number: 40 of 188 with model ARIMA for Validation 2
40 - ARIMA with avg smape 19.07: 
Model Number: 41 of 188 with model AverageValueNaive for Validation 2
41 - AverageValueNaive with avg smape 19.12: 
Model Number: 42 of 188 with model AverageValueNaive for Validation 2
42 - AverageValueNaive with avg smape 19.12: 
Model Number: 43 of 188 with model SeasonalNaive for Validation 2
43 - SeasonalNaive with avg smape 18.7: 
Model Number: 44 of 188 with model ARIMA for Validation 2
44 - ARIMA with avg smape 21.47: 
Model Number: 45 of 188 with model SeasonalNaive for Validation 2
45 - SeasonalNaive with avg smape 19.1: 
Model Number: 46 of 188 with model SectionalMotif for Validation 2
46 - SectionalMotif with avg smape 19.24: 
Model Number: 47 of 188 with model SeasonalNaive for Validation 2
47 - SeasonalNaive with avg smape 19.09: 
Model Number: 48 of 188 with model AverageValueNaive for Validation 2
48 - AverageValueNaive with avg smape 19.12: 
Model Number: 49 of 188 with model SectionalMotif for Validation 2
49 - SectionalMotif with avg smape 15.46: 
Model Number: 50 of 188 with model LastValueNaive for Validation 2
50 - LastValueNaive with avg smape 28.98: 
Model Number: 51 of 188 with model LastValueNaive for Validation 2
51 - LastValueNaive with avg smape 28.98: 
Model Number: 52 of 188 with model UnivariateMotif for Validation 2
52 - UnivariateMotif with avg smape 19.59: 
Model Number: 53 of 188 with model ConstantNaive for Validation 2
53 - ConstantNaive with avg smape 16.32: 
Model Number: 54 of 188 with model ConstantNaive for Validation 2
54 - ConstantNaive with avg smape 16.32: 
Model Number: 55 of 188 with model LastValueNaive for Validation 2
55 - LastValueNaive with avg smape 29.41: 
Model Number: 56 of 188 with model ConstantNaive for Validation 2
56 - ConstantNaive with avg smape 15.86: 
Model Number: 57 of 188 with model ConstantNaive for Validation 2
57 - ConstantNaive with avg smape 15.86: 
Model Number: 58 of 188 with model ConstantNaive for Validation 2
58 - ConstantNaive with avg smape 15.86: 
Model Number: 59 of 188 with model ConstantNaive for Validation 2
59 - ConstantNaive with avg smape 15.86: 
Model Number: 60 of 188 with model ConstantNaive for Validation 2
60 - ConstantNaive with avg smape 15.86: 
Model Number: 61 of 188 with model LastValueNaive for Validation 2
61 - LastValueNaive with avg smape 27.26: 
Model Number: 62 of 188 with model LastValueNaive for Validation 2
62 - LastValueNaive with avg smape 27.26: 
Model Number: 63 of 188 with model ARDL for Validation 2
63 - ARDL with avg smape 23.6: 
Model Number: 64 of 188 with model LastValueNaive for Validation 2
64 - LastValueNaive with avg smape 27.94: 
Model Number: 65 of 188 with model UnivariateMotif for Validation 2
65 - UnivariateMotif with avg smape 23.23: 
Model Number: 66 of 188 with model ConstantNaive for Validation 2
66 - ConstantNaive with avg smape 24.29: 
Model Number: 67 of 188 with model ConstantNaive for Validation 2
67 - ConstantNaive with avg smape 20.51: 
Model Number: 68 of 188 with model LastValueNaive for Validation 2
68 - LastValueNaive with avg smape 26.84: 
Model Number: 69 of 188 with model LastValueNaive for Validation 2
69 - LastValueNaive with avg smape 26.84: 
Model Number: 70 of 188 with model SeasonalNaive for Validation 2
70 - SeasonalNaive with avg smape 19.08: 
Model Number: 71 of 188 with model LastValueNaive for Validation 2
71 - LastValueNaive with avg smape 26.84: 
Model Number: 72 of 188 with model ARDL for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

72 - ARDL with avg smape 22.58: 
Model Number: 73 of 188 with model ARDL for Validation 2
73 - ARDL with avg smape 22.36: 
Model Number: 74 of 188 with model AverageValueNaive for Validation 2
📈 74 - AverageValueNaive with avg smape 6.44: 
Model Number: 75 of 188 with model AverageValueNaive for Validation 2
75 - AverageValueNaive with avg smape 19.12: 
Model Number: 76 of 188 with model AverageValueNaive for Validation 2
76 - AverageValueNaive with avg smape 19.12: 
Model Number: 77 of 188 with model SeasonalNaive for Validation 2
77 - SeasonalNaive with avg smape 20.06: 
Model Number: 78 of 188 with model ARDL for Validation 2
78 - ARDL with avg smape 23.46: 
Model Number: 79 of 188 with model SectionalMotif for Validation 2
79 - SectionalMotif with avg smape 16.39: 
Model Number: 80 of 188 with model MetricMotif for Validation 2
80 - MetricMotif with avg smape 16.53: 
Model Number: 81 of 188 with model ARDL for Validation 2
81 - ARDL with avg smape 23.37: 
Model Number: 82 of 188 with model ARDL for Validation 2
82 - ARDL with avg smape 23.36: 
Model Number: 83 of 188 with model ARDL for Validation 2
83 - ARDL with avg smape 23.36: 
Model Number: 84 of 188 with model ARDL for Validation 2
84 - ARDL with avg smape 23.36: 
Model Number: 85 of 188 with model MetricMotif for Validation 2
85 - MetricMotif with avg smape 19.28: 
Model Number: 86 of 188 with model MetricMotif for Validation 2
86 - MetricMotif with avg smape 18.29: 
Model Number: 87 of 188 with model MetricMotif for Validation 2
87 - MetricMotif with avg smape 17.43: 
Model Number: 88 of 188 with model UnivariateMotif for Validation 2
88 - UnivariateMotif with avg smape 18.47: 
Model Number: 89 of 188 with model UnivariateMotif for Validation 2
89 - UnivariateMotif with avg smape 18.47: 
Model Number: 90 of 188 with model MetricMotif for Validation 2
90 - MetricMotif with avg smape 17.21: 
Model Number: 91 of 188 with model UnivariateMotif for Validation 2
91 - UnivariateMotif with avg smape 14.21: 
Model Number: 92 of 188 with model MultivariateMotif for Validation 2
92 - MultivariateMotif with avg smape 19.47: 
Model Number: 93 of 188 with model MetricMotif for Validation 2
93 - MetricMotif with avg smape 15.58: 
Model Number: 94 of 188 with model MultivariateMotif for Validation 2
94 - MultivariateMotif with avg smape 18.96: 
Model Number: 95 of 188 with model MetricMotif for Validation 2
95 - MetricMotif with avg smape 25.66: 
Model Number: 96 of 188 with model ETS for Validation 2
96 - ETS with avg smape 19.12: 
Model Number: 97 of 188 with model UnivariateMotif for Validation 2
📈 97 - UnivariateMotif with avg smape 5.74: 
Model Number: 98 of 188 with model MetricMotif for Validation 2
98 - MetricMotif with avg smape 17.63: 
Model Number: 99 of 188 with model WindowRegression for Validation 2
99 - WindowRegression with avg smape 19.83: 
Model Number: 100 of 188 with model MetricMotif for Validation 2
100 - MetricMotif with avg smape 15.39: 
Model Number: 101 of 188 with model UnobservedComponents for Validation 2
101 - UnobservedComponents with avg smape 21.33: 
Model Number: 102 of 188 with model UnobservedComponents for Validation 2
102 - UnobservedComponents with avg smape 25.04: 
Model Number: 103 of 188 with model UnobservedComponents for Validation 2
103 - UnobservedComponents with avg smape 18.87: 
Model Number: 104 of 188 with model GLS for Validation 2
104 - GLS with avg smape 24.96: 
Model Number: 105 of 188 with model ETS for Validation 2
105 - ETS with avg smape 19.12: 
Model Number: 106 of 188 with model SeasonalNaive for Validation 2
106 - SeasonalNaive with avg smape 26.12: 
Model Number: 107 of 188 with model SeasonalNaive for Validation 2
107 - SeasonalNaive with avg smape 26.59: 
Model Number: 108 of 188 with model MultivariateMotif for Validation 2
108 - MultivariateMotif with avg smape 25.31: 
Model Number: 109 of 188 with model MultivariateMotif for Validation 2
109 - MultivariateMotif with avg smape 25.31: 
Model Number: 110 of 188 with model ETS for Validation 2
110 - ETS with avg smape 19.12: 
Model Number: 111 of 188 with model GLS for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\decomposition\_fastica.py:576: UserWarning:

Ignoring n_components with whiten=False.

111 - GLS with avg smape 26.29: 
Model Number: 112 of 188 with model SeasonalNaive for Validation 2
112 - SeasonalNaive with avg smape 28.39: 
Model Number: 113 of 188 with model SeasonalNaive for Validation 2
113 - SeasonalNaive with avg smape 28.39: 
Model Number: 114 of 188 with model UnobservedComponents for Validation 2
114 - UnobservedComponents with avg smape 19.12: 
Model Number: 115 of 188 with model UnobservedComponents for Validation 2
115 - UnobservedComponents with avg smape 19.11: 
Model Number: 116 of 188 with model ETS for Validation 2
116 - ETS with avg smape 19.12: 
Model Number: 117 of 188 with model ETS for Validation 2
117 - ETS with avg smape 19.22: 
Model Number: 118 of 188 with model UnobservedComponents for Validation 2
118 - UnobservedComponents with avg smape 16.03: 
Model Number: 119 of 188 with model UnobservedComponents for Validation 2
119 - UnobservedComponents with avg smape 18.94: 
Model Number: 120 of 188 with model UnobservedComponents for Validation 2
120 - UnobservedComponents with avg smape 19.17: 
Model Number: 121 of 188 with model UnobservedComponents for Validation 2
121 - UnobservedComponents with avg smape 19.17: 
Model Number: 122 of 188 with model UnivariateRegression for Validation 2
122 - UnivariateRegression with avg smape 22.47: 
Model Number: 123 of 188 with model DatepartRegression for Validation 2
123 - DatepartRegression with avg smape 25.62: 
Model Number: 124 of 188 with model GLM for Validation 2
124 - GLM with avg smape 19.13: 
Model Number: 125 of 188 with model DatepartRegression for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

125 - DatepartRegression with avg smape 26.1: 
Model Number: 126 of 188 with model GLM for Validation 2
126 - GLM with avg smape 19.13: 
Model Number: 127 of 188 with model ETS for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

127 - ETS with avg smape 19.12: 
Model Number: 128 of 188 with model ETS for Validation 2
128 - ETS with avg smape 19.12: 
Model Number: 129 of 188 with model MultivariateRegression for Validation 2
129 - MultivariateRegression with avg smape 20.54: 
Model Number: 130 of 188 with model ETS for Validation 2
130 - ETS with avg smape 19.16: 
Model Number: 131 of 188 with model ETS for Validation 2
131 - ETS with avg smape 19.16: 
Model Number: 132 of 188 with model DatepartRegression for Validation 2
132 - DatepartRegression with avg smape 20.19: 
Model Number: 133 of 188 with model Ensemble for Validation 2
133 - Ensemble with avg smape 25.54: 
Model Number: 134 of 188 with model MultivariateRegression for Validation 2
134 - MultivariateRegression with avg smape 21.2: 
Model Number: 135 of 188 with model GLM for Validation 2
135 - GLM with avg smape 19.12: 
Model Number: 136 of 188 with model SectionalMotif for Validation 2
136 - SectionalMotif with avg smape 8.79: 
Model Number: 137 of 188 with model GLM for Validation 2
137 - GLM with avg smape 27.83: 
Model Number: 138 of 188 with model SectionalMotif for Validation 2
138 - SectionalMotif with avg smape 19.34: 
Model Number: 139 of 188 with model SectionalMotif for Validation 2
139 - SectionalMotif with avg smape 7.77: 
Model Number: 140 of 188 with model GLM for Validation 2
140 - GLM with avg smape 30.04: 
Model Number: 141 of 188 with model GLS for Validation 2
141 - GLS with avg smape 19.07: 
Model Number: 142 of 188 with model WindowRegression for Validation 2
142 - WindowRegression with avg smape 19.11: 
Model Number: 143 of 188 with model DatepartRegression for Validation 2
143 - DatepartRegression with avg smape 20.55: 
Model Number: 144 of 188 with model DatepartRegression for Validation 2
144 - DatepartRegression with avg smape 20.55: 
Model Number: 145 of 188 with model GLM for Validation 2
145 - GLM with avg smape 19.12: 
Model Number: 146 of 188 with model GLS for Validation 2
146 - GLS with avg smape 19.05: 
Model Number: 147 of 188 with model GLS for Validation 2
147 - GLS with avg smape 19.12: 
Model Number: 148 of 188 with model GLM for Validation 2
148 - GLM with avg smape 19.12: 
Model Number: 149 of 188 with model GLM for Validation 2
149 - GLM with avg smape 27.91: 
Model Number: 150 of 188 with model GLM for Validation 2
150 - GLM with avg smape 19.19: 
Model Number: 151 of 188 with model GLS for Validation 2
151 - GLS with avg smape 19.09: 
Model Number: 152 of 188 with model DatepartRegression for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\generalized_linear_model.py:307: DomainWarning:

The InversePower link function does not respect the domain of the Gamma family.

152 - DatepartRegression with avg smape 20.83: 
Model Number: 153 of 188 with model GLS for Validation 2
153 - GLS with avg smape 19.12: 
Model Number: 154 of 188 with model DatepartRegression for Validation 2
154 - DatepartRegression with avg smape 20.84: 
Model Number: 155 of 188 with model GLS for Validation 2
155 - GLS with avg smape 19.12: 
Model Number: 156 of 188 with model DatepartRegression for Validation 2
156 - DatepartRegression with avg smape 19.12: 
Model Number: 157 of 188 with model UnivariateRegression for Validation 2
157 - UnivariateRegression with avg smape 11.11: 
Model Number: 158 of 188 with model DatepartRegression for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=2.11238e-41): result may not be accurate.

158 - DatepartRegression with avg smape 19.82: 
Model Number: 159 of 188 with model UnivariateRegression for Validation 2
159 - UnivariateRegression with avg smape 25.22: 
Model Number: 160 of 188 with model GLS for Validation 2
160 - GLS with avg smape 20.15: 
Model Number: 161 of 188 with model MultivariateRegression for Validation 2
161 - MultivariateRegression with avg smape 21.88: 
Model Number: 162 of 188 with model SectionalMotif for Validation 2
162 - SectionalMotif with avg smape 6.71: 
Model Number: 163 of 188 with model UnivariateRegression for Validation 2
163 - UnivariateRegression with avg smape 11.03: 
Model Number: 164 of 188 with model MultivariateRegression for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=2.11237e-41): result may not be accurate.

164 - MultivariateRegression with avg smape 21.73: 
Model Number: 165 of 188 with model UnivariateRegression for Validation 2
165 - UnivariateRegression with avg smape 19.75: 
Model Number: 166 of 188 with model WindowRegression for Validation 2
166 - WindowRegression with avg smape 18.99: 
Model Number: 167 of 188 with model MultivariateRegression for Validation 2
167 - MultivariateRegression with avg smape 18.95: 
Model Number: 168 of 188 with model MultivariateMotif for Validation 2
168 - MultivariateMotif with avg smape 19.06: 
Model Number: 169 of 188 with model MultivariateRegression for Validation 2
169 - MultivariateRegression with avg smape 14.67: 
Model Number: 170 of 188 with model UnivariateRegression for Validation 2
170 - UnivariateRegression with avg smape 19.74: 
Model Number: 171 of 188 with model UnivariateRegression for Validation 2
171 - UnivariateRegression with avg smape 19.8: 
Model Number: 172 of 188 with model UnivariateRegression for Validation 2
172 - UnivariateRegression with avg smape 19.83: 
Model Number: 173 of 188 with model UnivariateRegression for Validation 2
173 - UnivariateRegression with avg smape 17.98: 
Model Number: 174 of 188 with model MultivariateMotif for Validation 2
174 - MultivariateMotif with avg smape 17.37: 
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.65067e-25): result may not be accurate.

Model Number: 175 of 188 with model MultivariateMotif for Validation 2
175 - MultivariateMotif with avg smape 13.75: 
Model Number: 176 of 188 with model SectionalMotif for Validation 2
176 - SectionalMotif with avg smape 13.95: 
Model Number: 177 of 188 with model MultivariateMotif for Validation 2
📈 177 - MultivariateMotif with avg smape 2.58: 
Model Number: 178 of 188 with model MultivariateMotif for Validation 2
178 - MultivariateMotif with avg smape 21.82: 
Model Number: 179 of 188 with model SectionalMotif for Validation 2
179 - SectionalMotif with avg smape 19.98: 
Model Number: 180 of 188 with model MultivariateRegression for Validation 2
180 - MultivariateRegression with avg smape 24.05: 
Model Number: 181 of 188 with model MultivariateRegression for Validation 2
181 - MultivariateRegression with avg smape 25.23: 
Model Number: 182 of 188 with model WindowRegression for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

182 - WindowRegression with avg smape 21.52: 
Model Number: 183 of 188 with model WindowRegression for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

183 - WindowRegression with avg smape 21.31: 
Model Number: 184 of 188 with model MultivariateRegression for Validation 2
184 - MultivariateRegression with avg smape 21.96: 
Model Number: 185 of 188 with model WindowRegression for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

185 - WindowRegression with avg smape 18.01: 
Model Number: 186 of 188 with model WindowRegression for Validation 2
186 - WindowRegression with avg smape 24.53: 
Model Number: 187 of 188 with model WindowRegression for Validation 2
187 - WindowRegression with avg smape 21.01: 
Model Number: 188 of 188 with model WindowRegression for Validation 2
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.66699e-25): result may not be accurate.

188 - WindowRegression with avg smape 7.42: 
Validation Round: 3
Model Number: 1 of 188 with model Ensemble for Validation 3
📈 1 - Ensemble with avg smape 3.87: 
Model Number: 2 of 188 with model Ensemble for Validation 3
2 - Ensemble with avg smape 4.0: 
Model Number: 3 of 188 with model Ensemble for Validation 3
3 - Ensemble with avg smape 4.0: 
Model Number: 4 of 188 with model Ensemble for Validation 3
4 - Ensemble with avg smape 5.14: 
Model Number: 5 of 188 with model Ensemble for Validation 3
📈 5 - Ensemble with avg smape 2.21: 
Model Number: 6 of 188 with model Ensemble for Validation 3
6 - Ensemble with avg smape 2.27: 
Model Number: 7 of 188 with model ARIMA for Validation 3
📈 7 - ARIMA with avg smape 2.14: 
Model Number: 8 of 188 with model Theta for Validation 3
8 - Theta with avg smape 2.3: 
Model Number: 9 of 188 with model Theta for Validation 3
9 - Theta with avg smape 2.23: 
Model Number: 10 of 188 with model Theta for Validation 3
10 - Theta with avg smape 2.28: 
Model Number: 11 of 188 with model Ensemble for Validation 3
11 - Ensemble with avg smape 3.14: 
Model Number: 12 of 188 with model UnivariateMotif for Validation 3
12 - UnivariateMotif with avg smape 9.31: 
Model Number: 13 of 188 with model UnivariateMotif for Validation 3
13 - UnivariateMotif with avg smape 2.33: 
Model Number: 14 of 188 with model UnivariateMotif for Validation 3
14 - UnivariateMotif with avg smape 6.18: 
Model Number: 15 of 188 with model Theta for Validation 3
15 - Theta with avg smape 3.13: 
Model Number: 16 of 188 with model ARDL for Validation 3
16 - ARDL with avg smape 8.7: 
Model Number: 17 of 188 with model ARIMA for Validation 3
17 - ARIMA with avg smape 2.2: 
Model Number: 18 of 188 with model Theta for Validation 3
18 - Theta with avg smape 2.37: 
Model Number: 19 of 188 with model ARIMA for Validation 3
19 - ARIMA with avg smape 2.27: 
Model Number: 20 of 188 with model ARIMA for Validation 3
20 - ARIMA with avg smape 2.79: 
Model Number: 21 of 188 with model ARIMA for Validation 3
21 - ARIMA with avg smape 2.22: 
Model Number: 22 of 188 with model Theta for Validation 3
22 - Theta with avg smape 2.32: 
Model Number: 23 of 188 with model Theta for Validation 3
23 - Theta with avg smape 2.32: 
Model Number: 24 of 188 with model NVAR for Validation 3
24 - NVAR with avg smape 2.41: 
Model Number: 25 of 188 with model Theta for Validation 3
25 - Theta with avg smape 2.32: 
Model Number: 26 of 188 with model NVAR for Validation 3
26 - NVAR with avg smape 2.96: 
Model Number: 27 of 188 with model AverageValueNaive for Validation 3
27 - AverageValueNaive with avg smape 2.2: 
Model Number: 28 of 188 with model NVAR for Validation 3
28 - NVAR with avg smape 2.46: 
Model Number: 29 of 188 with model ARIMA for Validation 3
29 - ARIMA with avg smape 2.39: 
Model Number: 30 of 188 with model Theta for Validation 3
30 - Theta with avg smape 2.22: 
Model Number: 31 of 188 with model NVAR for Validation 3
31 - NVAR with avg smape 3.11: 
Model Number: 32 of 188 with model NVAR for Validation 3
32 - NVAR with avg smape 3.11: 
Model Number: 33 of 188 with model NVAR for Validation 3
33 - NVAR with avg smape 3.11: 
Model Number: 34 of 188 with model NVAR for Validation 3
34 - NVAR with avg smape 3.11: 
Model Number: 35 of 188 with model NVAR for Validation 3
35 - NVAR with avg smape 3.11: 
Model Number: 36 of 188 with model NVAR for Validation 3
36 - NVAR with avg smape 3.1: 
Model Number: 37 of 188 with model AverageValueNaive for Validation 3
37 - AverageValueNaive with avg smape 2.2: 
Model Number: 38 of 188 with model ARIMA for Validation 3
38 - ARIMA with avg smape 2.38: 
Model Number: 39 of 188 with model AverageValueNaive for Validation 3
39 - AverageValueNaive with avg smape 2.2: 
Model Number: 40 of 188 with model ARIMA for Validation 3
40 - ARIMA with avg smape 2.17: 
Model Number: 41 of 188 with model AverageValueNaive for Validation 3
41 - AverageValueNaive with avg smape 2.2: 
Model Number: 42 of 188 with model AverageValueNaive for Validation 3
42 - AverageValueNaive with avg smape 2.2: 
Model Number: 43 of 188 with model SeasonalNaive for Validation 3
43 - SeasonalNaive with avg smape 2.18: 
Model Number: 44 of 188 with model ARIMA for Validation 3
44 - ARIMA with avg smape 2.23: 
Model Number: 45 of 188 with model SeasonalNaive for Validation 3
45 - SeasonalNaive with avg smape 2.2: 
Model Number: 46 of 188 with model SectionalMotif for Validation 3
46 - SectionalMotif with avg smape 2.71: 
Model Number: 47 of 188 with model SeasonalNaive for Validation 3
47 - SeasonalNaive with avg smape 2.18: 
Model Number: 48 of 188 with model AverageValueNaive for Validation 3
48 - AverageValueNaive with avg smape 2.2: 
Model Number: 49 of 188 with model SectionalMotif for Validation 3
49 - SectionalMotif with avg smape 2.91: 
Model Number: 50 of 188 with model LastValueNaive for Validation 3
50 - LastValueNaive with avg smape 3.55: 
Model Number: 51 of 188 with model LastValueNaive for Validation 3
51 - LastValueNaive with avg smape 3.55: 
Model Number: 52 of 188 with model UnivariateMotif for Validation 3
📈 52 - UnivariateMotif with avg smape 2.13: 
Model Number: 53 of 188 with model ConstantNaive for Validation 3
53 - ConstantNaive with avg smape 2.29: 
Model Number: 54 of 188 with model ConstantNaive for Validation 3
54 - ConstantNaive with avg smape 2.29: 
Model Number: 55 of 188 with model LastValueNaive for Validation 3
55 - LastValueNaive with avg smape 3.85: 
Model Number: 56 of 188 with model ConstantNaive for Validation 3
56 - ConstantNaive with avg smape 2.56: 
Model Number: 57 of 188 with model ConstantNaive for Validation 3
57 - ConstantNaive with avg smape 2.56: 
Model Number: 58 of 188 with model ConstantNaive for Validation 3
58 - ConstantNaive with avg smape 2.56: 
Model Number: 59 of 188 with model ConstantNaive for Validation 3
59 - ConstantNaive with avg smape 2.56: 
Model Number: 60 of 188 with model ConstantNaive for Validation 3
60 - ConstantNaive with avg smape 2.56: 
Model Number: 61 of 188 with model LastValueNaive for Validation 3
61 - LastValueNaive with avg smape 4.19: 
Model Number: 62 of 188 with model LastValueNaive for Validation 3
62 - LastValueNaive with avg smape 4.16: 
Model Number: 63 of 188 with model ARDL for Validation 3
63 - ARDL with avg smape 5.98: 
Model Number: 64 of 188 with model LastValueNaive for Validation 3
64 - LastValueNaive with avg smape 4.67: 
Model Number: 65 of 188 with model UnivariateMotif for Validation 3
Template Eval Error: ValueError('Model UnivariateMotif returned NaN for one or more series. fail_on_forecast_nan=True') in model 65 in generation 0: UnivariateMotif
Model Number: 66 of 188 with model ConstantNaive for Validation 3
66 - ConstantNaive with avg smape 6.06: 
Model Number: 67 of 188 with model ConstantNaive for Validation 3
67 - ConstantNaive with avg smape 2.21: 
Model Number: 68 of 188 with model LastValueNaive for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\numpy\lib\function_base.py:551: RuntimeWarning:

invalid value encountered in divide

68 - LastValueNaive with avg smape 3.85: 
Model Number: 69 of 188 with model LastValueNaive for Validation 3
69 - LastValueNaive with avg smape 3.85: 
Model Number: 70 of 188 with model SeasonalNaive for Validation 3
70 - SeasonalNaive with avg smape 2.19: 
Model Number: 71 of 188 with model LastValueNaive for Validation 3
71 - LastValueNaive with avg smape 3.85: 
Model Number: 72 of 188 with model ARDL for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neighbors\_classification.py:233: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().

72 - ARDL with avg smape 3.6: 
Model Number: 73 of 188 with model ARDL for Validation 3
73 - ARDL with avg smape 3.34: 
Model Number: 74 of 188 with model AverageValueNaive for Validation 3
74 - AverageValueNaive with avg smape 16.82: 
Model Number: 75 of 188 with model AverageValueNaive for Validation 3
75 - AverageValueNaive with avg smape 2.2: 
Model Number: 76 of 188 with model AverageValueNaive for Validation 3
76 - AverageValueNaive with avg smape 2.2: 
Model Number: 77 of 188 with model SeasonalNaive for Validation 3
77 - SeasonalNaive with avg smape 2.42: 
Model Number: 78 of 188 with model ARDL for Validation 3
78 - ARDL with avg smape 5.55: 
Model Number: 79 of 188 with model SectionalMotif for Validation 3
79 - SectionalMotif with avg smape 5.63: 
Model Number: 80 of 188 with model MetricMotif for Validation 3
80 - MetricMotif with avg smape 3.64: 
Model Number: 81 of 188 with model ARDL for Validation 3
81 - ARDL with avg smape 5.91: 
Model Number: 82 of 188 with model ARDL for Validation 3
82 - ARDL with avg smape 5.91: 
Model Number: 83 of 188 with model ARDL for Validation 3
83 - ARDL with avg smape 5.91: 
Model Number: 84 of 188 with model ARDL for Validation 3
84 - ARDL with avg smape 5.91: 
Model Number: 85 of 188 with model MetricMotif for Validation 3
85 - MetricMotif with avg smape 2.88: 
Model Number: 86 of 188 with model MetricMotif for Validation 3
86 - MetricMotif with avg smape 4.79: 
Model Number: 87 of 188 with model MetricMotif for Validation 3
87 - MetricMotif with avg smape 7.0: 
Model Number: 88 of 188 with model UnivariateMotif for Validation 3
88 - UnivariateMotif with avg smape 7.54: 
Model Number: 89 of 188 with model UnivariateMotif for Validation 3
89 - UnivariateMotif with avg smape 7.54: 
Model Number: 90 of 188 with model MetricMotif for Validation 3
90 - MetricMotif with avg smape 4.82: 
Model Number: 91 of 188 with model UnivariateMotif for Validation 3
91 - UnivariateMotif with avg smape 4.84: 
Model Number: 92 of 188 with model MultivariateMotif for Validation 3
92 - MultivariateMotif with avg smape 3.71: 
Model Number: 93 of 188 with model MetricMotif for Validation 3
93 - MetricMotif with avg smape 2.8: 
Model Number: 94 of 188 with model MultivariateMotif for Validation 3
94 - MultivariateMotif with avg smape 3.5: 
Model Number: 95 of 188 with model MetricMotif for Validation 3
95 - MetricMotif with avg smape 15.07: 
Model Number: 96 of 188 with model ETS for Validation 3
96 - ETS with avg smape 2.2: 
Model Number: 97 of 188 with model UnivariateMotif for Validation 3
97 - UnivariateMotif with avg smape 16.45: 
Model Number: 98 of 188 with model MetricMotif for Validation 3
98 - MetricMotif with avg smape 2.47: 
Model Number: 99 of 188 with model WindowRegression for Validation 3
99 - WindowRegression with avg smape 2.48: 
Model Number: 100 of 188 with model MetricMotif for Validation 3
100 - MetricMotif with avg smape 2.72: 
Model Number: 101 of 188 with model UnobservedComponents for Validation 3
101 - UnobservedComponents with avg smape 2.93: 
Model Number: 102 of 188 with model UnobservedComponents for Validation 3
102 - UnobservedComponents with avg smape 5.01: 
Model Number: 103 of 188 with model UnobservedComponents for Validation 3
103 - UnobservedComponents with avg smape 2.14: 
Model Number: 104 of 188 with model GLS for Validation 3
104 - GLS with avg smape 3.3: 
Model Number: 105 of 188 with model ETS for Validation 3
105 - ETS with avg smape 2.2: 
Model Number: 106 of 188 with model SeasonalNaive for Validation 3
106 - SeasonalNaive with avg smape 4.89: 
Model Number: 107 of 188 with model SeasonalNaive for Validation 3
107 - SeasonalNaive with avg smape 4.63: 
Model Number: 108 of 188 with model MultivariateMotif for Validation 3
108 - MultivariateMotif with avg smape 4.63: 
Model Number: 109 of 188 with model MultivariateMotif for Validation 3
109 - MultivariateMotif with avg smape 4.63: 
Model Number: 110 of 188 with model ETS for Validation 3
110 - ETS with avg smape 2.2: 
Model Number: 111 of 188 with model GLS for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\decomposition\_fastica.py:576: UserWarning:

Ignoring n_components with whiten=False.

111 - GLS with avg smape 3.16: 
Model Number: 112 of 188 with model SeasonalNaive for Validation 3
112 - SeasonalNaive with avg smape 4.63: 
Model Number: 113 of 188 with model SeasonalNaive for Validation 3
113 - SeasonalNaive with avg smape 4.63: 
Model Number: 114 of 188 with model UnobservedComponents for Validation 3
114 - UnobservedComponents with avg smape 2.2: 
Model Number: 115 of 188 with model UnobservedComponents for Validation 3
115 - UnobservedComponents with avg smape 6.31: 
Model Number: 116 of 188 with model ETS for Validation 3
116 - ETS with avg smape 2.2: 
Model Number: 117 of 188 with model ETS for Validation 3
117 - ETS with avg smape 2.18: 
Model Number: 118 of 188 with model UnobservedComponents for Validation 3
118 - UnobservedComponents with avg smape 2.62: 
Model Number: 119 of 188 with model UnobservedComponents for Validation 3
119 - UnobservedComponents with avg smape 6.08: 
Model Number: 120 of 188 with model UnobservedComponents for Validation 3
120 - UnobservedComponents with avg smape 2.27: 
Model Number: 121 of 188 with model UnobservedComponents for Validation 3
121 - UnobservedComponents with avg smape 2.27: 
Model Number: 122 of 188 with model UnivariateRegression for Validation 3
122 - UnivariateRegression with avg smape 2.86: 
Model Number: 123 of 188 with model DatepartRegression for Validation 3
123 - DatepartRegression with avg smape 4.08: 
Model Number: 124 of 188 with model GLM for Validation 3
124 - GLM with avg smape 2.2: 
Model Number: 125 of 188 with model DatepartRegression for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

125 - DatepartRegression with avg smape 5.38: 
Model Number: 126 of 188 with model GLM for Validation 3
126 - GLM with avg smape 2.2: 
Model Number: 127 of 188 with model ETS for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\families\links.py:198: RuntimeWarning:

overflow encountered in exp

127 - ETS with avg smape 2.2: 
Model Number: 128 of 188 with model ETS for Validation 3
128 - ETS with avg smape 2.2: 
Model Number: 129 of 188 with model MultivariateRegression for Validation 3
129 - MultivariateRegression with avg smape 2.61: 
Model Number: 130 of 188 with model ETS for Validation 3
130 - ETS with avg smape 2.2: 
Model Number: 131 of 188 with model ETS for Validation 3
131 - ETS with avg smape 2.2: 
Model Number: 132 of 188 with model DatepartRegression for Validation 3
132 - DatepartRegression with avg smape 3.2: 
Model Number: 133 of 188 with model Ensemble for Validation 3
133 - Ensemble with avg smape 7.34: 
Model Number: 134 of 188 with model MultivariateRegression for Validation 3
134 - MultivariateRegression with avg smape 2.95: 
Model Number: 135 of 188 with model GLM for Validation 3
135 - GLM with avg smape 2.2: 
Model Number: 136 of 188 with model SectionalMotif for Validation 3
136 - SectionalMotif with avg smape 4.37: 
Model Number: 137 of 188 with model GLM for Validation 3
137 - GLM with avg smape 7.34: 
Model Number: 138 of 188 with model SectionalMotif for Validation 3
138 - SectionalMotif with avg smape 4.04: 
Model Number: 139 of 188 with model SectionalMotif for Validation 3
139 - SectionalMotif with avg smape 2.23: 
Model Number: 140 of 188 with model GLM for Validation 3
140 - GLM with avg smape 8.94: 
Model Number: 141 of 188 with model GLS for Validation 3
141 - GLS with avg smape 2.19: 
Model Number: 142 of 188 with model WindowRegression for Validation 3
142 - WindowRegression with avg smape 2.59: 
Model Number: 143 of 188 with model DatepartRegression for Validation 3
143 - DatepartRegression with avg smape 2.89: 
Model Number: 144 of 188 with model DatepartRegression for Validation 3
144 - DatepartRegression with avg smape 2.89: 
Model Number: 145 of 188 with model GLM for Validation 3
145 - GLM with avg smape 2.2: 
Model Number: 146 of 188 with model GLS for Validation 3
146 - GLS with avg smape 2.18: 
Model Number: 147 of 188 with model GLS for Validation 3
147 - GLS with avg smape 2.2: 
Model Number: 148 of 188 with model GLM for Validation 3
148 - GLM with avg smape 2.2: 
Model Number: 149 of 188 with model GLM for Validation 3
149 - GLM with avg smape 7.34: 
Model Number: 150 of 188 with model GLM for Validation 3
150 - GLM with avg smape 2.21: 
Model Number: 151 of 188 with model GLS for Validation 3
151 - GLS with avg smape 2.19: 
Model Number: 152 of 188 with model DatepartRegression for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\statsmodels\genmod\generalized_linear_model.py:307: DomainWarning:

The InversePower link function does not respect the domain of the Gamma family.

152 - DatepartRegression with avg smape 3.88: 
Model Number: 153 of 188 with model GLS for Validation 3
153 - GLS with avg smape 2.19: 
Model Number: 154 of 188 with model DatepartRegression for Validation 3
154 - DatepartRegression with avg smape 3.91: 
Model Number: 155 of 188 with model GLS for Validation 3
155 - GLS with avg smape 2.2: 
Model Number: 156 of 188 with model DatepartRegression for Validation 3
156 - DatepartRegression with avg smape 2.2: 
Model Number: 157 of 188 with model UnivariateRegression for Validation 3
157 - UnivariateRegression with avg smape 8.91: 
Model Number: 158 of 188 with model DatepartRegression for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=2.22864e-41): result may not be accurate.

158 - DatepartRegression with avg smape 2.49: 
Model Number: 159 of 188 with model UnivariateRegression for Validation 3
159 - UnivariateRegression with avg smape 6.48: 
Model Number: 160 of 188 with model GLS for Validation 3
📈 160 - GLS with avg smape 1.9: 
Model Number: 161 of 188 with model MultivariateRegression for Validation 3
161 - MultivariateRegression with avg smape 2.15: 
Model Number: 162 of 188 with model SectionalMotif for Validation 3
162 - SectionalMotif with avg smape 3.51: 
Model Number: 163 of 188 with model UnivariateRegression for Validation 3
163 - UnivariateRegression with avg smape 9.98: 
Model Number: 164 of 188 with model MultivariateRegression for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=2.22864e-41): result may not be accurate.

164 - MultivariateRegression with avg smape 3.73: 
Model Number: 165 of 188 with model UnivariateRegression for Validation 3
165 - UnivariateRegression with avg smape 2.39: 
Model Number: 166 of 188 with model WindowRegression for Validation 3
166 - WindowRegression with avg smape 2.13: 
Model Number: 167 of 188 with model MultivariateRegression for Validation 3
167 - MultivariateRegression with avg smape 2.42: 
Model Number: 168 of 188 with model MultivariateMotif for Validation 3
168 - MultivariateMotif with avg smape 8.94: 
Model Number: 169 of 188 with model MultivariateRegression for Validation 3
169 - MultivariateRegression with avg smape 3.11: 
Model Number: 170 of 188 with model UnivariateRegression for Validation 3
170 - UnivariateRegression with avg smape 2.39: 
Model Number: 171 of 188 with model UnivariateRegression for Validation 3
171 - UnivariateRegression with avg smape 2.4: 
Model Number: 172 of 188 with model UnivariateRegression for Validation 3
172 - UnivariateRegression with avg smape 2.4: 
Model Number: 173 of 188 with model UnivariateRegression for Validation 3
173 - UnivariateRegression with avg smape 6.89: 
Model Number: 174 of 188 with model MultivariateMotif for Validation 3
174 - MultivariateMotif with avg smape 4.77: 
Model Number: 175 of 188 with model MultivariateMotif for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.73648e-25): result may not be accurate.

175 - MultivariateMotif with avg smape 3.66: 
Model Number: 176 of 188 with model SectionalMotif for Validation 3
176 - SectionalMotif with avg smape 7.68: 
Model Number: 177 of 188 with model MultivariateMotif for Validation 3
177 - MultivariateMotif with avg smape 5.26: 
Model Number: 178 of 188 with model MultivariateMotif for Validation 3
178 - MultivariateMotif with avg smape 8.42: 
Model Number: 179 of 188 with model SectionalMotif for Validation 3
179 - SectionalMotif with avg smape 2.35: 
Model Number: 180 of 188 with model MultivariateRegression for Validation 3
180 - MultivariateRegression with avg smape 2.57: 
Model Number: 181 of 188 with model MultivariateRegression for Validation 3
181 - MultivariateRegression with avg smape 2.96: 
Model Number: 182 of 188 with model WindowRegression for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

182 - WindowRegression with avg smape 2.78: 
Model Number: 183 of 188 with model WindowRegression for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

183 - WindowRegression with avg smape 3.36: 
Model Number: 184 of 188 with model MultivariateRegression for Validation 3
184 - MultivariateRegression with avg smape 3.67: 
Model Number: 185 of 188 with model WindowRegression for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py:546: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html

185 - WindowRegression with avg smape 7.09: 
Model Number: 186 of 188 with model WindowRegression for Validation 3
186 - WindowRegression with avg smape 6.66: 
Model Number: 187 of 188 with model WindowRegression for Validation 3
187 - WindowRegression with avg smape 2.62: 
Model Number: 188 of 188 with model WindowRegression for Validation 3
C:\Users\YASHA KHANNA\.conda\anaconda\Lib\site-packages\sklearn\linear_model\_ridge.py:200: LinAlgWarning:

Ill-conditioned matrix (rcond=1.74902e-25): result may not be accurate.

188 - WindowRegression with avg smape 15.6: 
Model Number: 1834 with model Ensemble in generation 12 of Ensembles
Model Number: 1835 with model Ensemble in generation 12 of Ensembles
Model Number: 1836 with model Ensemble in generation 12 of Ensembles
Model Number: 1837 with model Ensemble in generation 12 of Ensembles
Model Number: 1838 with model Ensemble in generation 12 of Ensembles
Model Number: 1839 with model Ensemble in generation 12 of Ensembles
Model Number: 1840 with model Ensemble in generation 12 of Ensembles
Model Number: 1841 with model Ensemble in generation 12 of Ensembles
Validation Round: 1
Model Number: 1 of 8 with model Ensemble for Validation 1
📈 1 - Ensemble with avg smape 6.5: 
Model Number: 2 of 8 with model Ensemble for Validation 1
📈 2 - Ensemble with avg smape 6.42: 
Model Number: 3 of 8 with model Ensemble for Validation 1
3 - Ensemble with avg smape 7.01: 
Model Number: 4 of 8 with model Ensemble for Validation 1
4 - Ensemble with avg smape 7.44: 
Model Number: 5 of 8 with model Ensemble for Validation 1
📈 5 - Ensemble with avg smape 5.74: 
Model Number: 6 of 8 with model Ensemble for Validation 1
6 - Ensemble with avg smape 7.34: 
Model Number: 7 of 8 with model Ensemble for Validation 1
7 - Ensemble with avg smape 5.79: 
Model Number: 8 of 8 with model Ensemble for Validation 1
8 - Ensemble with avg smape 5.74: 
Validation Round: 2
Model Number: 1 of 8 with model Ensemble for Validation 2
📈 1 - Ensemble with avg smape 7.74: 
Model Number: 2 of 8 with model Ensemble for Validation 2
2 - Ensemble with avg smape 8.15: 
Model Number: 3 of 8 with model Ensemble for Validation 2
3 - Ensemble with avg smape 9.59: 
Model Number: 4 of 8 with model Ensemble for Validation 2
4 - Ensemble with avg smape 14.59: 
Model Number: 5 of 8 with model Ensemble for Validation 2
5 - Ensemble with avg smape 12.23: 
Model Number: 6 of 8 with model Ensemble for Validation 2
6 - Ensemble with avg smape 15.09: 
Model Number: 7 of 8 with model Ensemble for Validation 2
7 - Ensemble with avg smape 12.11: 
Model Number: 8 of 8 with model Ensemble for Validation 2
8 - Ensemble with avg smape 12.23: 
Validation Round: 3
Model Number: 1 of 8 with model Ensemble for Validation 3
📈 1 - Ensemble with avg smape 2.81: 
Model Number: 2 of 8 with model Ensemble for Validation 3
📈 2 - Ensemble with avg smape 2.51: 
Model Number: 3 of 8 with model Ensemble for Validation 3
3 - Ensemble with avg smape 2.51: 
Model Number: 4 of 8 with model Ensemble for Validation 3
📈 4 - Ensemble with avg smape 2.19: 
Model Number: 5 of 8 with model Ensemble for Validation 3
5 - Ensemble with avg smape 2.41: 
Model Number: 6 of 8 with model Ensemble for Validation 3
📈 6 - Ensemble with avg smape 2.15: 
Model Number: 7 of 8 with model Ensemble for Validation 3
7 - Ensemble with avg smape 2.39: 
Model Number: 8 of 8 with model Ensemble for Validation 3
8 - Ensemble with avg smape 2.41: 
                   Close
2024-01-18  43482.662978
2024-01-19  43531.837754
2024-01-20  43518.447435
2024-01-21  43376.327297
2024-01-22  43250.845972
2024-01-23  43191.246915
2024-01-24  42879.319311
2024-01-25  42765.399554
2024-01-26  42978.896859
2024-01-27  43144.721884
2024-01-28  43169.731392
2024-01-29  42994.647828
2024-01-30  42983.896955
2024-01-31  43066.325676
2024-02-01  43103.125566
2024-02-02  43157.053089
2024-02-03  43178.829129
2024-02-04  43301.285182
2024-02-05  43336.004907
2024-02-06  43339.993016
2024-02-07  43338.765843
2024-02-08  43281.653201
2024-02-09  43491.016422
2024-02-10  43544.124786
2024-02-11  43644.796782
2024-02-12  43635.442029
2024-02-13  43741.114994
2024-02-14  43988.514770
2024-02-15  43953.483233
2024-02-16  43806.659253
In [ ]: